ExtendSim Adopter Program

ExtendSim AdopterThese accredited institutions are giving their students a competitive edge by teaching simulation techniques and principles using the same product these students will use once they graduate... ExtendSim. Future engineers (civil, irrigation, cyber security, industrial, traffic systems, biochemical, construction, mining, etc.), business professionals (health care managers, policy & process managers, risk analysts, technology managers, economists, etc.), operations managers (service ops, supply chain, logistics planning, manufacturing systems, etc.), data & statistical analysts, and others are using ExtendSim to learn how simulation can help them advance in their careers.

Join these universities and adopt ExtendSim as THE simulation tool for your institution.

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Universidad Austral

Universidad AustralFacultad de Ingenieria
Maestría en Gestión de Operaciones

Pilar, Buenos Aires, Argentina

 

Course ExtendSim is used in Adopter since 2015
  Simulación Discreta
Prof. Victor Herrero
Student head count
  35 to 40 Postgraduate students working toward a Masters in Operations Management
How ExtendSim typically is used in the course
  The objective of the course is to provide the basic knowledge necessary to handle the techniques of simulation methods by discrete, dynamic and complex events to pose and solve typical problems of queues, waiting times and other operational phenomena with the help of computer simulation tools such as ExtendSim, with the purpose of being able to design specific logistic and productive systems and to evaluate hypothetical situations with the use of the resources involved. Students must solve cases through group work. Specifically, at course completion, students should be able to:
  Master complex problems using specific modeling techniques as well as simulation and computational optimization to find efficient solutions.
  Make management decisions based on the use of these techniques.
  Lead the activities of an organization in the areas of Operations, Supply Chain, and Projects.
Student Projects
  During the course the students solve 5 cases:
    Case 1: Manufacture of Printed Circuits
    Case 2: Manufacture of two Products with three components each
    Case 3: Manufacture of 2 Products with 3 components with set-up times
    Case 4: Manufacture of 3 products with tables of values of the transformation times. Random demand
    Final exam: Improvement of a process in the face of certain imposed conditions
Ease with which students learn to model with ExtendSim
  As it is a matter of a postgraduate course where the previous background of the students can be diverse, normally it requires at the beginning a leveling of the basic concepts (of systems, statistics, techniques of data analysis, process analysis, etc.), then venture deep into those corresponding to simulation itself. Depending on such diversity, the ease with which students learn the modeling and simulation techniques may vary, sometimes adding additional support classes is required.

Learning curve depends on each student's previous curricular training. In general, they incorporate the use of basic software in two or three meetings The greatest difficulty is in understanding the processes and in representing them. There is a tendency to use the software without sufficient prior analysis.
Benefits attained through the use of ExtendSim
  Become familiar with the various applications in relation to operations simulation
  How to study a system and understand its variables and parameters
  Knowledge of methods to model and simulate computer operations
  How to manage variability and make decisions based on computer simulated results
  Take sensitivity of the behavior of the processes to different conditions and to the variation of behavioral factors
Other comments
  When the size and complexity of the model grow (and then the number of blocks), the simulation speed is significantly affected. The base programming could be improved to optimize memory consumption.
    Imagine That Inc. response -- We are always working to optimize the efficiency of models. Part of what gives ExtendSim its strength is that it is a compiled application...the downside of that is that sometimes it might take a bit longer to run a model. But it shouldn't be that bad. Sometimes there are certain model building techniques that might slow a model down. We would be happy to look at the model that is running slowly for you to see if there might be some slight modifications we could suggest that might increase the simulation speed. Please send your model to our Support Department at https://www.extendsim.com/support/troubleshooting/support and ask them to help you figure out what might be slowing the run speed down.

Universidad de Piura

UDEPSchool of Engineering
Faculty of Industrial and Systems Engineering

Piura, Peru

Course ExtendSim is used in Adopter since 2020
  Simulación
Prof. Bertha Susana Vegas Chiyón
Type of course
  30 Junior & Senior students
How ExtendSim was used in the course
  ExtendSim was used by 24 students in the Spring of 2020 workshops. They learned techniques of Discrete Event Simulation; such as Items, Properties and Values; Queueing; Processing; Batching and Unbatching; Routing; Statistics and Metrics. They also solved some problems assigned by the professor.
Student projects
  The projects fulfilled by students have been intermediate and complex cases related to:
Warehouse system
Emergency room
Factory
Ease with which students learn to model with ExtendSim
  The level of the course was intermediate and, at this point, the students have had a successful development.
Benefits attained through the use of ExtendSim
  The benefits of the use of ExtendSim are the facility of representing processes, understanding them and, more importantly, experimenting with them in order to obtain data that can help with the decision making of the Industrial and Systems Engineering students.

Universidad de Talca

Universidad de TalcaIngeniería Civil Industrial Department
Curicó, Chile

Course ExtendSim is used in Adopter since 2021
  Procesos Estocásticos y Simulación
Prof. Myriam Gaete
Typical number of students
  20 students
How ExtendSim is used in the course
  The Stochastic Processes and Simulation course covers two competencies:
  Modeling operations systems that allow correct decision-making with existing resources in any organization.
  Design operations systems for the efficient and effective generation of goods and services.
Student projects
  Students simulated a case study of a museum.
Ease with which students learn to model with ExtendSim
  Students learned to use ExtendSim in less than 3 months. 
Benefits attained through the use of ExtendSim
  Students learned to simulate different types of processes using logic.

Universidad ORT Uruguay

ORT UruguayFacultad de Ingeniería
Sistemas de Informacíon

Montevideo, Uruguay

Course ExtendSim is used in Adopter since 2019
  Quantitative Methods for Business
Prof. Helena Garbarino
Type of course
  46 undergraduate students
How ExtendSim was used in the course
  We use ExtendSim in uncertainty scenarios combined with mathematical simulation (MonteCarlo method) to simulate and optimize processes and make recommendations to a decision maker.
Student projects
  Students do two types of projects:
  Individual and small cases during the semester.
  A final integrating project done in groups of 3 students.
Ease with which students learn to model with ExtendSim
  It has a learning curve that is difficult at first but then quickly accelerates.
Benefits attained through the use of ExtendSim
  Allows simulating and optimizing probabilistic processes and comparing results with those found using mathematical methods. In addition, because is a visual tool, it facilitates the understanding of the studied scenarios.

Universita Di Roma "La Sapienza"

Universita Di Roma La Sapienza

School of Management & Decision Sciences
Department of Science & Statistics

Rome, Italy

Courses ExtendSim is used in Adopter since 2011
  Business Process Reengineering - MAT 09
Dati Reti e Sistem - SECS S01
Paolo Dell'Olmo
Type of course
  Masters courses with 15-30 students, depending on the course
How ExtendSim typically is used in the course
  This is a short note on the adoption of ExtendSim software in the classes of Data, Networks & Systems and Business Process Reengineering of the Master program in Data Intelligence and Strategic Decisions.

For both cases the students used ExtendSim Simulation software to design and analyse some service networks which simulated a variety of systems (including Post Offices, Emergency Services, Web Servers, and so on).

At the end of each course, the students, working in small groups of two to four people, had to realize a simulation project of a realistic (existing) system, performing data collection, distribution analysis, and model validation and verification.

Universität Duisburg-Essen

Universitat Duisburg-Essen

Lehrstuhl Für Wirtschaftsprüfung, Unternehmensrechnung und Controlling
Auditing, Managerial Accounting and Control

Essen, Germany

Course ExtendSim is used in Adopter since 2012
  Operatives Controlling
Prof. Dr. Ludwig Mochty
Type of course
  Graduate with 142 students
How ExtendSim typically is used in the course
  ExtendSim is used as a tool for teaching the dynamic aspects of problems arising in the field of managerial control. ExtendSim plays a pivotal role within the Curriculum of this course and will continue to do so in the future. 
Student projects
  Students have to design and implement their own models for different case studies.
Ease with which students learn to model with ExtendSim
  By using a self-developed manual, students found an easy access to ExtendSim.
Benefits attained through the use of ExtendSim
  A deeper understanding of the dynamic aspects of managerial control as opposed to traditional comparative static models presented in typical textbooks. The graphical user interface and the possibility to use items of the different predefined libraries is the best aspect of using this software.

University of Alberta

alberta

Alberta School of Business
Department of Accounting, Operations, & Information Systems
Edmonton, AB Canada

Course ExtendSim is used in Adopter since 2012
  Simulation & Computer Modeling Techniques in Management - OM 422/622
Chris Neuman
Type of course
  Undergraduate with 35 students
How ExtendSim typically is used in the course
  The second half of the course is an introduction to discrete event simulation. Students used ExtendSim to complete a group project, one quiz, and two assignments.
Student projects
  The final project required students to develop a model of a retail service facility and to examine the impacts of various service changes (operating hours, policies affecting arrival and service rates) on various performance metrics. Past projects include a group project requiring students to model a barbershop and use the model to investigate the impact of shift schedules on various system metrics.
Ease with which students learn to model with ExtendSim
  Students appeared to understand how to model relatively quickly, which was impressive given it was not only their first introduction to Extendsim but to visual simulation in general.
Benefits attained through the use of ExtendSim
  With Extendsim, students were able to move quickly from zero experience to building reasonably complicated models. They also learned the benefits of visualization when eliciting buy-in from decision makers. Having ExtendSim allowed students to put their theoretical learning about discrete event simulation to use in a way that encourages them to retain the information.

Students benefited from hands-on experience with commercial-level software and developed an appreciation for the skills that go into creating a model, as well as the benefits of DES as an analytical tool for complex systems. The ability to quickly construct models using blocks and connectors. This enables rapid prototyping as well as good experience. It allows me to coach students to create a basic model first, then add complexity on an incremental basis.
Other comments
  We really appreciate the opportunity to use this software in the course. The feedback we have gotten from students makes clear that they find access to software like this a valuable addition to the course.

University of Auckland

University of Auckland

Faculty of Engineering
Department of Civil & Environmental Engineering
Auckland, New Zealand

Course ExtendSim is used in Adopter since 2011
  Discrete Event Simulation in Construction - Civil 792
Vicente Gonzalez
Type of course
  Masters course with 10-12 students
How ExtendSim typically is used in the course
  Used to teach how to build up simulation models of construction operations.
Student projects
  Simulation of Construction Projects
Ease with which students learn to model with ExtendSim
  Relatively easy.
Benefits attained through the use of ExtendSim
  ExtendSim provides flexibility for students to develop models and ability to visualize data. They are able to model complex production scenarios in construction by using the object-oriented structure of ExtendSim.

University of British Columbia

University of British Columbia

University of British Columbia
Norman B. Keevil Institute of Mining Engineering
Vancouver, BC Canada

Course ExtendSim is used in Adopter since 2014
  Modeling & Simulation - MINE350 & MINE553
W. Scott Dunbar
Student head count
  45-60 third year students, depending on the semester
How ExtendSim typically is used in the course
  ExtendSim is being used for the simulation of mining and mineral processing operations. It's also being used to illustrate methods for simulation of continuous and discrete event industrial processes for problem solving purposes. Also used to illustrate the use of probability models and to model logistics in mine operations and flows in mineral processing plants.

During the course, we solve 2 problems using continuous modeling and a third with discrete event modeling. Each requires estimating the distributions and probabilities of the outputs of models with random inputs. This can be done analytically in two of the problems. Simulation using ExtendSim is required for the other problem. 
Student projects
Shovel-truck logistics in an open pit
Spread of an epidemic
Vancouver airport
Mine concentrator plant
Flows in flotation circuits
Simulation of mine haulage shovel operations with complex fleet assignment schemes 
Simulation of mine tailings runout as a result of an impoundment breach
Simulation of a mine maintenance system
Model of control of crusher circuit
Simulation of mineral processing
Ease with which students learn to model with ExtendSim
  There is a short learning curve. Students are fairly proficient in building discrete event models with ExtendSim within less than 1 week. Starter tutorial given. Some also programmed blocks. The students were first-time users of ExtendSim and found it very easy to use. Within a month students understood the basics of discrete event simulation.
Benefits attained through the use of ExtendSim
  Rapid understanding of how to model and effects of random variables. Increased understanding of the role of random processes in industrial systems. ExtendSim has a simple, yet intuitive interface with good examples. It gives students a better understanding of probability and uncertainty, plus boosts their confidence in modeling difficult problems. It gives them a deep understanding of modeling and models for mineral resources.

University College London

londonSchool of Engineering
The Advanced Centre of Biochemical Engineering

London, UK

Course ExtendSim is used in Adopter since 2012
  Bioprocess Systems Engineering
Dr. Stephen Goldrick
Student head count
  30 to 40 Masters level students
How ExtendSim typically is used in the course
  To introduce the concepts of stochastic simulation and discrete-event simulation.
  Application of discrete-event simulation to biopharmaceutical manufacturing systems and processes.
  Plus, it is used in practical hands-on sessions.
  Uncertainty analysis
  Bottleneck analysis
  Manufacturing simulation
Student projects
  Application of discrete-event simulation to biopharmaceutical manufacturing systems and processes.
  Build DES models to evaluate biopharmaceutical manufacturing systems
  Improving efficiency of a biopharmaceutical production plant. Model building, presentation, and discussion of results.
  Analysing the current manufacturing process of a biopharma manufacturer, using a discrete-event simulation model, and providing recommendations about possible improvement alternatives to implement.
  Development of bioprocess manufacturing simulation models.
  Implementation of bioprocesses for drug manufacturing
  Identification of bottlenecks
  Implementation of process improvements
Ease with which students learn to model with ExtendSim
  Very easily. Easy to understand and enjoy seeing the simulation move objects.
Benefits attained through the use of ExtendSim
  Ability to quickly obtain insights into stochastic systems. Hands on, easy understanding of discrete-event and stochastic simulation. Creates an awareness of advantages of discrete-event simulation techniques, plus the animation gives students the ability to understand the flow of entities and results of model assumptions in the design and evaluation of alternative manufacturing processes.

Using ExtendSim added a new set of skills to students, not previously provided within the course.

University of Colorado - Boulder

University of ColoradoLeeds School of Business
Department of Management
Boulder, CO USA

Courses ExtendSim is used in Adopter since 2016
  Business Process Analytics and
Business Process Analysis
Prof. Marco Better, PhD
Type of course
  Masters course with up to 30 students
How ExtendSim typically is used in each course
  In the Business Process Analytics course, ExtendSim is being used to model as-is processes, test improvement ideas, validate theoretical aspects, and to provide solutions in a practical project.

The second half of the Business Process Analysis course was dedicated to the concepts and practice of simulating business processes, and ExtendSim is the tool used to teach simulation.
Student projects
  In 2019, 6 class group projects on real-world examples from different industries were required, in addition to various simulation modeling assignments.

In past years, students had to complete 5 weekly assignments involving using ExtendSim to simulate part of a business process, and a final project where they used the tool to model a complex process as-is, and to experiment with process redesign and improvement.
Ease with which students learn to model with ExtendSim
  They found ExtendSim to be very intuitive, easy to learn, and easy to use.
Benefits attained through the use of ExtendSim
  Students develop knowledge in a tool that will be useful in students' future careers. The tool is very "intuitive" compared to other commercially available competitor products. It is easy to visualize the flow of items in a flowchart-like design workspace. Students were able to see the ease of use and value of a simulation-based approach to process measurement and redesign. They can easily validate current process, experiment with proposed re-designs and improvements.
Additional comments
  The Adopter program is an excellent way to have a win-win situation for the University, the students and ExtendSim!

University of Houston - Clear Lake

UHCLCollege of Science & Engineering
Systems Engineering Program

Houston, TX USA

Course ExtendSim is used in Adopter since 2020
  Systems Engineering Analysis and Modeling
Prof. James B Dabney
Anticipated students
  10 to 20 graduate students
How ExtendSim is used in the course
  ExtendSim is used as the main tool for students to learn to develop discrete event simiulations.
Student projects
  Students use ExtendSim on homework assignments and approximately 50% of studetns use it on their course project. Additionally, approximately 40% of the students use Extend on their capstone project.
Ease with which students learn to model with ExtendSim
  The students pick up ExtendSim very quickly and produce good quality simulations.
Benefits attained through the use of ExtendSim
  The students learn to model complex discrete event systems with multiple parallel and sequential queues and servers.
Other comments
  ExtendSim is a valuable resource in my class and I'm grateful for the opportunity to share it with my students.

University of Indianapolis

University of Indianapolis

School of Business
Data Analytics Department
Indianapolis, IN USA

Courses ExtendSim is used in Adopter since 2012
  Systems & Process Analysis
Information Systems Projects
Jerry Flatto
Type of course
  Undergraduate course
How ExtendSim typically is used in each course
  Systems & Process Analysis course was based around ExtendSim and had students develop a variety of simulations, including some that included costs.

Students in the Information Systems Projects course use software, including ExtendSim, for system analysis, physical design, programming, testing, and implementation of a database system.
Student projects
  Grocery store customer flow and queueing process
  X-ray facility
  Adoption process in the Humane Society
  Basketball
  Airport security
  Car wash
  Bank management
  Major project modeling
Ease with which students learn to model with ExtendSim
  For the students willing to put in the effort, it was pretty easy. The built-in help on the blocks and the user manual were very helpful.
Benefits attained through the use of ExtendSim
  It is easy to use. The graphical interface makes visualizing the process easier to understand. The block-based method of creating models by connecting blocks together to build more complex models is one of the best aspects of using ExtendSim. It p rovided the students an appreciation of how simulation can assist in decision making.
Others courses using ExtendSim
  University of Indianapolis has developed a new Master of Science program in Applied Analytics. In the summer of 2019, ExtendSim was used for prescriptive analysis in some of their MBA courses.

University of Iowa

University of Iowa

Tippie College of Business
Business Analytics Department
Iowa City, IA USA

Course ExtendSim is used in Adopter since 2013
  Operations Management
Prof. Jeffrey Ohlmann
Type of course
  Undergraduate course with 435 students
How ExtendSim typically is used in the course
  ExtendSim used as part of team project to simulate a business process.
Student projects
  Yes. One course project. Students not required to build model from scratch. Only take functioning model and modify it.
Ease with which students learn to model with ExtendSim
  ExtendSim very user-friendly.
Benefits attained through the use of ExtendSim
  ExtendSim is a great tool to "visualize" impact of uncertainty and countermeasures to address it.

ExtendSim is also used in  
  Business Process Analysis - MSCI 3030
Jeffrey Ohlmann and Michael Altemeier
Type of course
  Undergraduate course with 180 students
How ExtendSim typically is used in the course
  Students use ExtendSim to model business processes and gauge impact of improvement ideas. It is used for homework assignments, lab exercises, and examinations.
Student projects
  Students completed homework assignments and a Kaizen project using ExtendSim. Plus, the final exam is administered in the computer lab using ExtendSim.

In addition to this course, ExtendSim is being used by the Tippie Analytics Cooperative for more advanced projects. The Tippie Analytics Cooperative works with national and international brands to creatively solve some of the most challenging problems facing business today. Clients come from nearly every industry vertical and represent organizations of all sizes. In one of the more recent projects, Patient flow and optimization - University of Iowa Hospitals and Clinics, students from the Tippie Analytics Cooperative worked with massive amounts of patient encounter data to reveal bottlenecks and opportunities as patients arrive and flow through the multiple engagements that constitute an appointment. Insights provided by the students help UIHC improve the patient experience by driving operational efficiencies, optimizing staffing, and streamlining patient visits.
Ease with which students learn to model with ExtendSim
  Moderate learning curve. I create video tutorials on specific ExtendSim logic. Students are directed in weekly lab sessions for in-person help. The combination of these two things allow students to learn ExtendSim well.
Benefits attained through the use of ExtendSim
  Relatively user-friendly, but still flexible enough to model real problems. The point-and-click interface of ExtendSim makes it easy to get started. Students can see the effects of variability and the impact of process improvement efforts to directly observe course concepts (queueing, impact of variability, process improvement, etc.). It allows students to test and observe.

University of Mons

University of MonsEngineering Faculty
Department of Systems, Estimation, Control, & Optimization

Mons, Belgium

Course ExtendSim is used in Adopter since 2018
  Discrete Event Systems
Prof. Alain Vande Wouwer
Student head count
  Up to 12 Masters level students
How ExtendSim typically is used in the course
  ExtendSim is used to illustrate discrete event modeling and solve small-size discrete-event simulation problems. Students are asked to complete a project using ExtendSim.
Student projects
  Students used ExtendSim to develop a simulation of a manufacturing line located on the technological campus. Students had to collect data from the line, build models, develop an integrated simulator, and study the various configurations that could be envisioned to improve productivity and reduce the occurrence of failures or product rejects.
Ease with which students learn to model with ExtendSim
  The software is easy to use and learn. Students can easily learn the use of ExtendSim and apply it to the problems and projects.
Benefits attained through the use of ExtendSim
  The graphical interface is convenient and easy to use. The learning curve of ExtendSim is good, and all the basic tools are available for discrete-time simulation.

University of Moratuwa

University of Moratuwa

Faculty of Engineering and Technology
UNESCO Madanjeet Singh Center for South Asia Water Management
Moratuwa, Sri Lanka

Course ExtendSim is used in Adopter since 2016
  Irrigation Engineering
Prof. N.T.S. Wijesekera
Type of course
  Masters course with approximately 25 students
How ExtendSim typically is used in the course
  ExtendSim was used to teach the post graduate students how to model an irrigation reservoir and associated cultivation area for sustainable water management and to identify important physical properties and water management techniques and practices for irrigation system design, planning and operation with the use of ExtendSim tools.
Student projects
  Students individually developed their own ExtendSim model with the lecturer giving step by step guidance to develop an irrigation reservoir operation model using ExtendSim.
Ease with which students learn to model with ExtendSim
  Student recognized the graphical interface as a versatile tool compared to the normally used spreadsheet type models.
Benefits attained through the use of ExtendSim
  The advantage for the students is the ability to easily incorporate a variety of concepts. This is a very important feature in case of water resources management. Post graduate students are impressed by the use of advanced modelling tools for our teaching in the Masters of Water Resources Engineering Program. This enhances the status of our University. 

University of North Carolina Wilmington

University of North Carolina Wilmington

Cameron School of Business
Information Systems & Operations Management Department
Wilmington, NC USA

Course ExtendSim is used in Adopter since 2015
  Introduction to Computer Simulation - QMM 485
Barry A. Wray
Type of course
  Undergraduate course with 12 students
How ExtendSim typically is used in the course
  Primary simulation package used in the course. Students learn fundamental concepts, such as:
  Introduction to simulation and models
  Discrete event simulation
    -Queuing model
    -Inventory control model
  Probability and statistical testing
  Random number generation
  Generating random variables from discrete and continuous probability distributions
  Terminating simulations
  Steady-state simulation
  Analysis of experimental results from computer simulations
  Application of simulation using ExtendSim
  Modeling basic operations and inputs
  Develop animated displays of complex systems
  Modeling detailed operations
  Course project
  Identify and analyze a business system to model
  Build a simulation model using ExtendSim
  Run the model and generate experimental data
  Analyze the data generated by the model
  Interpret the results
  Build an implementation plan
Student projects
  Homework, quizzes, tests, and a final project.
Benefits attained through the use of ExtendSim
  The advantage of ExtendSim is the graphical nature of its interface (blocks/connections). And that students learn to use simulation.

University of Rochester

rochester

Simon School of Business
Rochester, NY USA

Course ExtendSim is used in Adopter since 2010
  Service Operations - OMG 412
Phillip J. Lederer
Type of course
  Second year MBA elective course taken by 20-32 students
How ExtendSim typically is used in the course
  ExtendSim is a central part of the course. It is used to supporting notions of service operations models highlighting service flow, capacity planning, bottleneck analysis, just the concept of what a discrete event simulation means and how to interpret the statistics.

The software fits quite well into the topic of the course which was managing service systems. In terms of applications, the package was used by students to model various service operations. Many of the cases were based upon Harvard Business School cases (BAT, Benihana, CVS).
  A car wash (an exercise from ExtendSim examples).
  Police dispatching policies for patrol cars.
  Planning capacity for a drive up gas station/convenience store.
  Managing a technical call center and priority rules (BAT case).
  Capacity analysis of a restaurant (Benihana of Tokyo).
  Process improvement of a retail drug store (CVS case).
  Modeling services in a bakery, barber shop, and supermarket.
  Organizing a salesforce (Baria Harvard Case)
  pdf buttonClick here for an example of a typical homework assignment.
Training materials
  I was greatly aided by Robin Clark who shared his knowledge of ExtendSim with me.

I continued to make tutorial videos to help my students learn ExtendSim. I added a couple of new ones on more detailed issues.

I created a couple of new videos. The most important was on interpreting statistical results. Here I show that events in ExtendSim simulations are correlated so that the Central Limit theorem does not hold. This is important to note when viewing averages and variances output.
Ease with which students learn to model with ExtendSim
  Most mastered it. With my video tutorials they pick it up rather quickly. The ones who put in the effort, find success.
Benefits attained through the use of ExtendSim
  Fundamental is learning the benefits and limitiations of simulation. Using ExtendSim strengthened students analytic ability. Students learned to do simulation. The visual interface of ExtendSim is its most attractive feature. 
Additional comments
  I appreciate the support of the company when I get stuck trying to model activities or am confused about a feature.

University of Southern California

University of Southern California

Marshall School of Business
Department of Data Sciences and Operations
Los Angeles, CA USA

Course ExtendSim is used in Adopter since 2011
  Discrete Event  Simulation for Process Management
Prof. Amy Ward
Type of course
  Graduate course with approximately 45 students
How ExtendSim typically is used in the course
  This is a half-course focused entirely on Discrete-Event Simulation. The course is derived from an earlier full semester course, Simulation for Business Analytics. That course was split into half-semester courses.
Student projects
  There is a project for this course, required to be done in ExtendSim.
Ease with which students learn to model with ExtendSim
  Fine.
Benefits attained through the use of ExtendSim
  It is reasonably intuitive to get started, once the basics of discrete-event simulation are known. The user interface is the best aspect of ExtendSim.

Additionally, ExtendSim has been used in the following course
  Simulation for Business Analytics - IOM 599
Prof. Amy Ward
Type of course
  Graduate course with 30 students
How ExtendSim typically is used in the course
  The approach of this new course was to build simulation models to answer practical questions that are motivated by business decisions. For example, simulation was used to:
  Estimate the return of an index-based stock market portfolio.
  Determine if project deadlines could be met.
  Decide on the staffing level and workload division in a service system.
  Locate company production facilities.
  Over the course of building these simulation models, both the power of simulation and some of its pitfalls and limitations were discovered.

The course consisted of:
  Lecture
  Homework assignments
  Take-home assignments
  Project
Student projects
  One end-of-term group project. Each group had 4 to 5 students. Various applications (inventory management, call center, etc) were represented by each group
Ease with which students learn to model with ExtendSim
  Really depended on how comfortable the student felt with prob/stat and modeling.
Benefits attained through the use of ExtendSim
  The class was a mix of non-technical MBA students and more technical Masters students interested in Analytics. I am not sure I could have done discrete event simulation without the easy graphic interface.

Additionally, ExtendSim has been used in the following course
  Dynamic Programming and Markov Decision Processes - IOM 677
Prof. Amy Ward
Type of course
  PhD course with 6 students
How ExtendSim typically is used in the course
  Sequential decision making under uncertainty. ExtendSim will be used to simulate policy performance, especially in cases where the problem is not tractable analytically.

I devoted one course lecture (3 class hours), on Friday April 13, to teaching the students how to use ExtendSim. In this lecture, the students learned how to build the model in the paper by Levent Kocaga and myself, Admission Control for a Multi-Server Queue with Abandonment, in ExtendSim. This was a very nice use of ExtendSim, because we were able to show that the theoretical results and approximations developed in Kocaga and Ward matched the ExtendSim simulations.

The lecture on ExtendSim was given by Dave Krahl of Imagine That Inc. and Robin Clark from QMT Group. Dave and Robin additionally showed the students much more advanced models that could be built using ExtendSim. I asked the students for feedback on this lecture, and they said that they found the lecture very useful.

It was possible for Dave and Robin to give the lecture because they were already in the Los Angeles area for an INFORMS conference. Hence it made sense to arrange for them to give a half-day open ExtendSim session to users in the Los Angeles area, and then another half-day session oriented directly for the students in my IOM 677 course.

The course IOM 677 is intended for PhD students, and there were 6 PhD students enrolled in the course. Part of my inteneded purpose in teaching ExtendSim is that I believe it can be useful for the students as they pursue their PhD research. I have used ExtendSim many times myself in my own research, in order to validate theoretical approximations or test proposed policies, and have been very satisfied. Therefore, I wanted the students to be aware of how they could use this in their own research. Although I did not have a specific homework problem that involved ExtendSim (because simulation is a little off-topic for a Markov Decision Process Course), I feel comfortable that that goal was achieved.

Thank you very much for giving me the opportunity to be an ExtendSim Adopter. I hope to be able to continue this status in the future.

Additionally, ExtendSim has been used in the following course
  Queueing and Stochastic Networks - IOM 674
Prof. Amy Ward
Type of course
  PhD course wtih 9 candidates
How ExtendSim typically is used in the course
  Queueing phenomena that arise in engineering and business systems will be modeled and analyzed in this course. The queueing is generated by resource contention when there is uncertainty.

Early on in the course, I devoted one lecture to the basics of using ExtendSim, and demonstrated to the students how to build a couple basic queueing models in ExtendSim. We then discussed how to estimate performance measures for those models such as the mean time in queue. This allowed me to assign homework problems to the students that required the use of ExtendSim. The problems I assigned were as follows:
  HW #2, Problem 4.
    The students were asked to find the limiting probabilities, and the expected number of customers waiting at each station, for a particular Jackson network configuration. This can be done through exact analytic formula (and that exact analysis was taught in class). The students were then asked to simulate the network using ExtendSim, and to see that their simulation answers matched their analytic answers.
  HW #4, Problem 2.
    The students were asked to develop a heavy-traffic approximation for the mean number of customers in the system for a GI/GI/1 queue, under two different distributional assumptions for the service times that were not exponential. Note that there are no exact analytic formulae for steadystate performance measures for this system, and so the students had to rely on approximation formulae (which we developed in class). The students were then asked to simulate the GI/GI/1 queue using Extend in order to understand the situations in which their approximation formulae performed well.
  HW #4, Problem 3.
    The students were asked to develop a heavy traffic approximation for the mean number of customers at each station in a network that consisted of two GI/GI/1 queues in tandem. Again, there are no exact analytic formulae available and so the students had to rely on approximation formulae. The students were then asked to simulate the network using Extend in order to see how their approximation formulae performed.
Benefits attained through the use of ExtendSim
  I view the use of ExtendSim as very important for the course. In order for the students to truly understand how to develop and use analytic approximation formulae for queueing networks that cannot be analyzed exactly, it is extremely helpful for them to also simulate the network. The simulation allows them to understand how to apply their approximation formulae to estimate performance measures of interest, and to know when there approximation formulae will work well vs when their approximation formulae may not work well. Please also see my Homeworks #2 and #4 for the exact questions referenced above.

I am very appreciative for having the use of ExtendSim for this course. Thank you.

University of Split

University of Split

Faculty of Economics, Business, & Tourism
Department for Information Technology in Management
Split, Croatia

Course ExtendSim used in Adopter since 2014
  Business Process Simulation
Mario Jadric
Type of course
  Masters course with 25-35 students
How ExtendSim typically is used in the course
  ExtendSim is used to demonstrate as well as practice business process simulation modelling by the students. Students were presented ExtendSim tool, which they used to deliver business process models for process optimization.

ExtendSim was used for:
  Presentation of the course and planned activities.
  Modeling of complex systems.
  Concept of simulation.
  Approaches to simulation modeling.
  Types of computer simulation.
  The selection of simulation models.
  Business processes and simulation modeling
  Projects of simulation modeling.
  Choosing a process for simulation modeling.
  Theory of waiting queues.
  Distribution of random variable in simulation modeling.
  Discrete event simulation.
  Construction of discrete simulation model.
  Planning simulation experiments.
  Analysis of simulation results.
  Concepts of business process management and simulation modeling.
  The concepts of system dynamics
  Analysis of casual loops.
Student projects
  Discrete event simulation modeling using ExtendSim - exercise series.
  Modeling of complex systems.
  Waiting queues.
  Distribution of random variables in simlation modeling.
  Construction of discrete simulation models.
  Analysis of simulation results.
  Final course project - case study of real life project realization, modeling as-is and to-be real life processes.
  Business process simulation and optimization, plus bottleneck detection and optimization.
Ease with which students learn to model with ExtendSim
  Students had no issues with learning simulation considering the tutorials & videos are in-depth. ExtendSim is an intuitive yet powerful modelling tool. Also, help and manuals available for the tool are very helpful. Besides, example models are great!
Benefits attained through the use of ExtendSim
  Simulation modelling understanding & awareness for beginners and experts. Hands-on practical approach. Acquiring basic modelling knowledge as well as Discrete Event Simulation realization for our students. In-depth understanding of simulation and what-if analysis benefits for different industries. Students learned how to design processes, objects, attributes and methodology used in ExtendSim. Showing benefits of designing to-be processes of current business situation, designing as-is situation, performing analysis and designing to-be situation using advanced business process modelling. Performing what-if analysis.

Thumbs up for the great tool, demo examples/use cases as well as help files and exercises!

University of Tennessee - Knoxville

University of Tennessee Knoxville

Haslam College of Business
Department of Business Analytics & Statistics
Knoxville, TN USA

Course ExtendSim is used in Adopter since 2011
  Simulation Modeling - BZAN 546
Bogdan Bichescu
Type of course
  Graduate course
How ExtendSim has been used in the course
  BZAN 546 is a graduate class taught in the College of Business Administration at the University of Tennessee and focuses on modeling business processes using discrete-event simulation software. As part of the class, students built simulation models relating to the management of inventories, waiting lines, and various resources, in contexts such as healthcare, retail banking, and manufacturing. Moreover, students used ExtendSim on four homework assignments, end-of-term class projects, and the course final which dealt with capacity planning and optimization for a hospital’s outpatient clinic. Some of the course projects include:
bulletBus scheduling and routing for a large, on-campus, youth creativity competition
bulletCapacity planning and optimization for a hospital’s outpatient clinic

In summary, the use of ExtendSim in the class:
  1 exposed students to an industry-leading discrete-event simulation environment.
  2 demonstrated the application of simulation concepts in an integrated, GUI-driven application environment (including elements of problem abstraction and modeling, sensitivity analysis and experimentation, heuristic optimization, animation and visualization, etc.).
  3 helped students develop an intuitive, visual understanding of system dynamics (in contrast to, for example, formal treatments of resource management in the form of traditional queueing models).
  4 afforded students the ability to easily and quickly perform sensitivity analyses for system improvement.
  5 improved students’ problem solving techniques and their ability to grasp the importance of robustness and flexibility as system design principles.

Additionally, ExtendSim has been used in the following course
  Decision Analytics & Simulation - MS 532
Melissa Bowers & Bogdan Bichescu
How ExtendSim typically is used in the course
  MS 532 is a graduate class taught in the College of Business Administration at the University of Tennessee and the better part of the class curriculum focuses on modeling business processes using discrete-event simulation software. As part of the class, students built simulation models relating to the management of inventories, waiting lines, and various resources, in contexts such as healthcare, retail banking, and manufacturing. Moreover, students used ExtendSim on two homework assignments and one end-of-term class project, which dealt with capacity planning and optimization for a medical device manufacturer. In summary, the use of ExtendSim in the class:
  1 exposed students to an industry-leading discrete-event simulation environment.
  2 demonstrated the application of simulation concepts in an integrated, GUI-driven application environment (including elements of problem abstraction and modeling, sensitivity analysis and experimentation, heuristic optimization, animation and visualization, etc.).
  3 helped students develop an intuitive, visual understanding of system dynamics (in contrast to, for example, formal treatments of resource management in the form of traditional queueing models).
  4 afforded students the ability to easily and quickly perform sensitivity analyses for system improvement.
  5 improved students’ problem solving techniques and their ability to grasp the importance of robustness and flexibility as system design principles.

University of Washington

University of WashingtonFoster School of Business
Department of Information Systems & Operations Management

Seattle, WA USA

Course ExtendSim is used in Adopter since 2017
  OMGT502: Introduction to Operations Management
Professor Apurva Jain
Type of course
  MBA with approximately 100 students
How ExtendSim is used in the course
  This evening MBA core course is an introduction to Operations Management that is designed to:
  Prepare students to see the world in terms of flows of work and material
  Provide students with models and concepts to analyze these flows
  Offer students practice in the application of these models to generate improvement ideas
  Motivate students to spot opportunities for such improvements in their workspace
  ExtendSim will be used to:
  Show bottlenecks
  Queueing concepts
  Possibly push vs. pull
Possible ExtendSim use in other courses
  Possibly SCM 513: Operations Management and Process Analysis

University of Western Australia

University of Western AustraliaBusiness School
Department of Management & Organisations

Perth, WA, Australia

Course ExtendSim will be used in Adopter since 2019
  Models for Logistics, Operations, and Services - INMT5518
Prof. Peter Goldschmidt
Anticipated students
  This is a post-graduate unit, usually 25-30 students, but it reached 40 in the past.
Course summary
  This unit introduces the primary models used to optimise the supply chain. It develops students' capacity to define a problem for modelling, specify models and apply appropriate software packages. Topics include transport and transhipment models; warehouse location decisions; inventory optimisation; simulating the supply chain; simple forecasting models; management of quality and timeliness, including service encounters; and database design for operations.

Students will be able to:
(1) design and develop a database for operations management and decision making;
(2) evaluate computer models for business decisions;
(3) apply management science tools to business applications;
(4) demonstrate proficiency in specialised management science software; and
(5) develop written and oral communication skills.
Simulation concepts to be taught in the course
  Simulation
  Simuland
  Types of simulations
  Stochastic processes
  Data
  Assumptions and boundaries
  Verification and validation
  Scenario analysis
Projects to be fulfilled by the students using ExtendSim
  Various assignments, including simulation supply chains for various products, airport terminals, timetable rail, port and trans-shipment, project management (discrete event).
  Attempts of generic simulations and system dynamics.
  In the past, we have also run optimisations.
ExtendSim use outside of this course
  PhD students will also be using ExtendSim for their projects.

University of Wisconsin - Madison

University of Wisconsin

Wisconsin School of Business
Department of Operations & Information Management 
Madison, WI USA

Course ExtendSim is used in Adopter since 2013
  Service Operations Management
Professor Robert Batt
Student head count
  Up to 71 undergrad & 36 MBA/Graduate level students
How ExtendSim typically is used in the course
  ExtendSim is used to teach basic queuing principles such as how wait time explodes as utilization approaches 1, non-linear response to server count, non-linear relationship of utilization and wait time and the benefit of pooled vs. separated servers. The students perform both in class exercises as well larger homework case analysis. We build simple queues, multi-channel queues, tandem queues, etc. We explore queue performance under different conditions. We looked at topics such as drivers of queue time, the impact of priorities, and the impact of batching.
Student projects
  We start with building simple M/M/c queues, and then add complexity such as priorities, pooled vs. separated queues, and then eventually do the HBS Delwarca Call Center case.
  Mini-cases of a car wash and a barber shop learning impact of variability, utilization, pooling queues, priorities, etc.
  Spent two days analyzing and improving a call center using the "Delwarca Software Remote Support Unit" case from Harvard Business School (HBS) Publishing.
  In the past, used the BAT and Benihana cases from HBS Publishing.
  Plus a few instructor-created exercises.
  A new HBS case was added in 2021: "Breakfast at the Paramount" by Ryan Buell. Prof. Buell's note don't include simulation, so I had to design the questions and assignments, but it worked really well to look at bottlenecks and customer priorities. I highly recommend it.
Ease with which students learn to model with ExtendSim
  It's always a mixed bag. Some take to it quite easily, and some really struggle. But that's true of all the quantitative topics I do. But overall, most students are able to build and manipulate queues fairly quickly. The basics are easy. Some more sophisticated things, such as batching, are more difficult. Some students get it instantly. Some struggle constantly. I don't think the variance is due to the software.
Benefits attained through the use of ExtendSim
  Students get to build an manipulate queues themselves. We get to do much more complex designs than if we were limited to simple queueing formulas. We can go MUCH farther than with simple M/M/c equations. Students can design and test very complex queues quite quickly testing lots of ideas. I can teach the students much more complicated concepts (priorities, batching, etc) than I could if I stuck to Little's Law and simple M/M/c type queue equations. Students get to build their own queues and see the various performance metrics change as the students change the parameters and queue flow/design. The students can be set loose to experiment and try different ideas to improve service systems.

Wake Forest University

Wake Forest UniversitySchool of Business
Master of Business Analytics

Winston-Salem, NC, USA

Course ExtendSim is used in Adopter since 2019
  Simulation and Risk Analysis - BAN 7050
Prof. Dan Harris
Student head count
  66 graduate students
How ExtendSim typically is used in the course
  This course was originally created by Dr Stephen Powell and covers the use of static and dynamic simulation to help manage risk.
Student projects
  No specific projects unless students choose to use it as part of their support or analysis of their Action Learning Project (ALP).
Ease with which students learn to model with ExtendSim
  Initial class showed positive results so much that we would prefer to use ExtendSim again rather than Arena.
Benefits attained through the use of ExtendSim
  Compute and visually understand simulation concepts such as Monte Carlo simulation, Dynamic simulation, Distribution fitting, Statistical analysis of simulation output, and simulation/optimization for decision making.
Future plans for ExtendSim at Wake Forest
  We could see utilization of ExtendSim in our residential MSBA program, our online MSBA program, and our UG business courses. Students could also use it as part of their ALP (Action Learning Project) prior to completion of the program.
Additional comments
  Looking forward to getting to know the software package better since I am using it for the very first time.

Wroclaw University of Science & Technology

Wroclaw University of TechnologyFaculty of Computer Science & Management
Department of Operations Research & Business Intelligence
Wroclaw, Poland

Course ExtendSim is used in Adopter since 2010
  Simulation Modeling
Jacek Zabawa
Type of course
  Masters course with approximately 50 students, sometimes up to 100 students
ExtendSim use in 2021
  Wroclaw 2021During the classes in which I used ExtendSim (compared to the previous year) I added a model in which I presented a way to implement the assumptions about the 2 automated teller machine operating system. We assumed there were two customer streams. In the first stream of people (client 1) the client selects this ATM (atm1 or atm2) to which there is a shorter queue – I presented the use of blocks Max&Min, Select Item Out (control via connector Select). In the second stream of people (client 2) can only use atm2. In addition, I showed how to model the failure of the ATM (Shutdown block). I also presented setting numeric attribute values (rodzaj_klienta; Set and Random Number blocks) and used attribute values to control random time distribution parameters (in Activity block).

After each meeting with students, I checked the acquired knowledge by collecting answers to sample questions, such as:

  • Which block is used to model service stations?
  • How can you model a case in which the distribution of servie time at the server depends on te value of the specified attribute but the distribution type is always the same?
  • What information can we get from the History block?
How ExtendSim typically is used in the course
  This software was used as a primary modeling tool for continuous and discrete event-simulation software. Students build a simple model on their own and work in teams of two to build a model based on assumptions.
Student projects
  It depends on the number of the course hours. During the course of 10 hours, students develop a model based on the assumptions in the form of text using a graphical representation of the model (in the Extendsim notation) and complement the model with the ability to record the results of several runs.

During the course of 15 hours, students develop two models for an evaluation. First, on the basis of the assumptions in the form of text, and using the graphical representation of the model (it is kind of a test designed to realize the student's skill level). Then prepare a complete model based on assumptions and graphical representation other than Extendsim). It is a task carried out in groups of two students.
Ease with which students learn to model with ExtendSim
  Very fine, easy GUI, input and output connectors, easy handling of attributes.
Benefits attained through the use of ExtendSim
  ExtendSim is powerful software in which we can build very complex models, develop our own library of blocks, and it has good integration with external data. We also appreciate its:
  Easy handling of attributes and their processing.
  High correspondence between the model and the structure of the process.
  Hierarchical blocks.
2020- aspects of building models of discrete event systems presented in the course
    MODEL 1
The simplest model consistent with the discrete (queuing) approach. The possibility of displaying charts was also presented.
    MODEL 2
The simplest model equipped with the ability to save the results of many experiments and simple statistical calculations.
    MODEL 3
Automatic sensitivity analysis and the possibility of cloning interior windows.
    MODEL 4
Controlling the length of service time using an external RANDOM NUMBER block and connector D at the service station (ACTIVITY).
    MODEL 5
Presentation of using the SELECT ITEM OUT switch to direct objects that do not fit in a queue to another place. Note the impact of this solution on the simulation results.
    MODEL 6
Model extension with a preparatory service module. It was shown how to combine two streams, how to declare attributes and their values, how to check the values of attributes in a selected place of the model, how to draw a path for objects.
    MODEL 7
Presentation of static attribute attribution (in the path all objects will have the same attribute value). You can also see in the HISTORY block the simultaneous possession of two different attributes by a given object (attributes: color and I_STep = yes / no).
    MODEL 11
Wroclaw 2020 modelThe completion (batching) technique was presented. In batching, we combine objects (it can come from different sources) and treat the rest of the model as a whole. However, objects can be separated at the selected place in the model. An example of using the batching technique is modeling employee participation in material processing.
Sample of ExtendSim usage in past courses
    Wroclaw sample model 1LESSON 1
Create an input stream in which the exponential time between arrivals is, on the average, 10 minutes. Set up a buffer that can accommodate a queue of 100 objects for a set of service stations. Each station can process 3 objects at the same time. Service time is a triangular distribution with a minimum of 8, maximum of 15, and average of 12 minutes. Check the length of the queue when the model is run 4 times for 6 hours each.

wroclaw18 2LESSON 2
Using Global Arrays and Named Connections, take note of the number of objects output at the end of each of the runs, the final waiting time in the queue, and its average value.

LESSON 3
There are four types of items (A, B, C, & D) requiring prep work prior to servicing. Types A, B, & C are generated on an average of one every 10 minutes on an exponential distribution. The likelihood of each type being generated is:
      30%
      40%
      30%
Type D is generated one every 10 minutes. Tip: Store information about each item’s type as a 'Type' attribute.

Prep work servicing for types A and C is performed on 3 dedicated servers. Prep time is a triangular distribution of between 5 and 10 minutes with 8 being the highest probability. Priority prepping is given to type A items.

Prep work servicing for types B and D is performed on 2 dedicated servers. Prep time for type B is a triangular distribution of between 5 and 10 minutes with 8 being the highest probability. Prep time for type D is a triangular distribution of between 5 and 14 minutes with 8 being the highest probability.

Determine how many items are generated by the system and how many of each type. Wroclaw

Tip: Use Information (Item), Select Item Out (Item), and Select Item In (Item) blocks in addition to the Data Source Create and Write blocks.

LESSON 4: Batching
There are four employees at the workshop. Unless there is an employee available, service at any station cannot begin or end. At the end of each service activity, employees rest up and begin to get acquainted with the next activity at their station (this process takes 10 minutes). As the most valuable resource, the employee is only called into service with the item they will be working on is available for service.

Wroclaw - lesson 4Are four employees enough to maximize productivity? Or should the company hire more? Or would a reduction in staff be more beneficial?

Additionally, ExtendSim has been used in the following course
  Business Modeling and Forecasting
Jacek Zabawa
How ExtendSim typically is used in the course
  I introduced the experiment (a change in the way the classes). At the first session I showed (and students to repeat) how to build a very simple queuing model equipped with the ability to record the results of multiple runs (blocks a write). At the second class I presented high degree of complexity model (service attributes, batching, recurrences of objects). At the third class I presented sets of simple models which implement (separately) service attributes and batching. These models were gradually expanded. Students build simple models and then expanded them. At the next class (in January) will be a single test, performed independently, consisting of self-construction of a simple model based on the assumptions of text. I'll put the suggestions (hints) on the types of blocks that can be used. Before the test I'll do recap material. At the last class students who do not pass the test will be able to fix it. For those who have passed positively I would like to present other advanced capabilities Extendsim, perhaps it will be genetic optimization or sensitivity analysis.

Additionally, ExtendSim was used in the following course
  Financial Analysis of Company Appliations with Models
Jacek Zabawa
How ExtendSim typically was used in the course
  It consisted of a lectures and seminars. During lectures I presented, among others, new edition of complete application in Extendsim allowing construction of financial statements (balance, incomes etc.). As in the previous year we also discussed its modules, such as the calculation of income and expenses for this activity-based costing. We tried to use the models for business game support.

In the seminar portion of the course, students created financial simulation models of selected economic games. Here, the tool was arbitrary, but some groups chose to implement their model in ExtendSim - due to the readability of models created in ExtendSim was particularly didactic.

Preparing for this course inspired Prof. Zabawa to prepare another paper in  to formulate a methodology of modeling assumptions in financial simulations. This methodology is based on the multiplication of objects: one object for "things" and second object for "money". "Integrating discrete event simulation and financial reporting" was accepted for publication and it was presented during the 33rd International Conference Information Systems and Technology Architecture.

I used the previously improved structure of the lecture with several recordings (movies snap) on how to create models. I have presented different models for the problem of "improving equipment" and how to study the impact of such change on the financial statements. As in the previous year, we dealt with economic events "prepayment" and "delay in payment of liabilities and receivables". I also presented the design and calculation techniques of balance statement using yogurt production model that was included in the package ExtendSim.

Conference papers submitted based on Prof. Zabawa's projects
Jacek Zabawa, Bozena Mielczarek (2021)"An attempt to replace system dynamics with discrete rate modeling in demographic simulations. W: Computational Science - ICCS 2021 : 21st International Conference Krakow, Poland, June 16-18, 2021 : proceedings. Pt. 4 / eds. Maciej Paszynski [i in.]. Cham : Springer, cop. 2021. s. 269-283. (Lecture Notes in Computer Science, ISSN 0302-9743; vol. 12745) DOI 10.1007/978-3-030-77970-2_21
    Abstract: The usefulness of simulation in demographic research has been repeatedly confirmed in the literature. The most common simulation ap-proach to model population trends is system dynamic (SD). Difficulties in a reliable mapping of population changes with SD approach have been howev-er reported by some authors. Another simulation approach, i.e. discrete rate modeling (DRM), had not yet been used in population dynamics modelling, despite examples of this approach being used in the modelling of processes with similar internal dynamics. The purpose of our research is to verify if DRM can compete with the SD approach in terms of accuracy in simulating population changes and the complexity of the model. The theoretical part of the work describes the principles of the DRM approach and provides an overview of the applications of the DRM approach versus other simulation methods. The experimental part permits the conclusion that DRM approach does not match the SD in terms of comprehensive accuracy in mapping the behavior of cohorts of the complex populations. We have been however able to identify criteria for population segmentation that may lead to better re-sults of DRM simulation against SD.
 Zabawa J. (2020) "Simulation Approach in Queue Management at Supermarkets in the COVID-19 Era". Presented at the 35th IBIMA Conference, Seville, Spain. 1-2 April 2020.
    Abstract: How to prevent and control of epidemic spreading of diseases (for example COVID-19) in supermarkets? To answer this question, a simulation approach was proposed. A number of simulation experiments were performed. The likelihood of close contact with carrier in different ticket queue configurations was compared. Based on the results, several tips and suggestions were developed for customers and market managers.
Mielczarek B., Zabawa J. (2018) "Modelling Population Dynamics Using a Hybrid Simulation Approach: Application to Healthcare". In: Obaidat M., Ören T., Merkuryev Y. (eds) Simulation and Modeling Methodologies, Technologies and Applications. SIMULTECH 2016. Advances in Intelligent Systems and Computing, vol 676. Springer, Cham, cop. 2018. s. 241-260
ISBN    978-3-319-69831-1
    Abstract: The goal of the study is presenting a population submodel developed using the system dynamics (SD) approach and discussing solutions for the integration of the SD methodology with discrete time control in formulating long-term projections for population evolution and its influence on healthcare demand. This study relies on historical demographic data and officially formulated scenarios for the most likely population projections for the Wrocław Region. The historical parameters are applied from 2002 to 2014, and projected trends are adopted for 2015 to 2035. The preliminary findings confirm the validity of using the hybrid simulation approach for a more advanced exploration of demography-dependent health policy issues.
Bożena Mielczarek, Jacek Zabawa. "Simulation model for studying impact of demographic, temporal, and geographic factors on hospital demand". Winter Simulation Conference, 2017
    Abstract: This paper reports on the results of a study that aims to develop the hybrid simulation model for estimating the level and structure of the demand for healthcare services. Research is performed for the Wrocław Region (WR), the main administrative area of Lower Silesia, the fourth largest province in Poland. An aging chain approach is implemented in the system dynamic model to forecast the number of individuals belonging to the respective age-gender cohorts over the next 20 years. The discrete event simulation model predicts the expected volume of emergency arrivals at the WR hospitals and explores the relations between demand and demographical, temporal and geographical aspects. The projections of long-term population evolutions are performed on the aggregated data and analysis is focused on pre-specified age-gender cohorts. The demographic groups are described using parameters such as birth and death rates, life expectancy, and migration descriptors. The historical data on hospital admissions are drawn from National Health Fund regional branch registry. Findings have important implications for the future decisions on distributions of the resources on the regional level.
Bozena Mielczarek, Jacek Zabawa. "Modelling Population Growth, Shrinkage and Aging using a Hybrid Simulation Approach: Application to Healthcare". SIMULTECH 2016: 75-83
    Abstract: This paper describes a hybrid simulation model that integrates the System Dynamic approach with discrete time control to formulate the projections of population evolution. The study relies on historical demographic data and the officially formulated scenarios for the most likely population projections developed for the region. The results of the simulation experiments provide valuable insights into dynamics of regional demographic trends and offer a well-defined starting point for future research in the health policy field. The intensity and structure of the demand for healthcare services depend heavily on age-gender profiles that change due to ongoing extensions of the average expected length of life, the aging of population, the continuing trend of declining number of births and the steadily growing number of deaths. The preliminary findings show promise in using the hybrid simulation approach for more advanced exploration of demography dependent health policy issues.
Bozena Mielczarek, Jacek Zabawa. "Modeling Healthcare Demand Using a Hybrid Simulation Approach". Winter Simulation Conference 2016.
    Abstract: This paper describes a hybrid simulation model that uses a system dynamics and discrete event simulation to study the influence of long-term population changes on the demand for healthcare services. A dynamic simulation model implements an aging chain approach to forecast the number of individuals who belong to their respective age-sex cohorts. The demographic parameters that were calculated from a Central Statistical Office Local Data Base were applied to the Wroc?aw Region population from 2002 to 2014, and the basic scenario for the projected trends was adopted for a time horizon from 2015 to 2035. The historical data on hospital admissions were obtained from the Regional Health Fund. A discrete event model generates batches of patients with cardiac diseases and modifies the demand according to the demographic changes that were forecasted by a population model. The results offer a well-defined starting point for future research in the health policy field.
Jacek Zabawa, Edward Radosinski. "Comparison of discrete rate modeling and discrete event simulation. Methodological and performance aspects." Published in Springer's book series: Advances in Intelligent Systems and Computing
Jacek Zabawa. "Discrete rate modeling approach for supply chain modeling" Presented at the Total Logistic Management Conference 2015 and published in the Czasopismo Logistyka journal in 2016.
    Abstract: The paper discusses the basics of modeling inventory management system in a spreadsheet. Then the application of a discrete rate in the supply chain simulation was proposed. Assumptions of test models which utilize DRM was presented. The structure of models and specification requirements was proposed. Selected simulation experiments were performed. The results were analyzed in a specially designed spreadsheet tool. Conclusions and prospects for further research was presented.
Bozena Mielczarek, Jacek Zabawa, and Marek Lubicz. "A System Dynamics Model to Study the Impact of an Age Pyramid on Emergency Demand." In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, 879-888, 2014, Vienna, Austria
    Abstract: This paper describes a system dynamics simulation model to analyse the relationship between age pyramid and the volume of patients arriving to hospital emergency departments located in a sub-region of Lower Silesia of Poland. The study relies on demographic and historical demand data, and the cohort forecasts for the population of the region. The results of the simulation experiments provide insights into the relationship between sub-regional demographic trends and population needs in relation to hospital emergency arrivals. The preliminary findings indicate that the forecasted long-term demographic changes in the population may increase the number of emergency patients in the area.

Zurich University of Applied Sciences (ZHAW)

ZHAW School of Engineering

School of Engineering
Institute of Data Analysis and Process Design
Winterthur, Switzerland

Courses ExtendSim is used in Adopter since 2011
  Simulation of Business Processes
Traffic System Operation
Professor Manuel Renold
Student head count
  60 to 75 advanced and professional students in various classes
Overview of courses
  The SoBP course is an introduction to discrete event simulation. Its goal is to teach the basic concepts of discrete event simulation then have students apply these concepts to practical problems.

The first four weeks of this course are a technical introduction to ExtendSim (libraries: Item, Value, Chart). For the rest of the course, ExtendSim is used as the workhorse for many applications and exercises that are built around the conceptual concepts taught. Students model assembly lines, passenger simulations, and optimization problems (GA-Optimizer is very helpful).
Projects fulfilled by students using ExtendSim
  Used for Bachelors and Masters Theses
  Airport simulations
  Passenger flows
  Optimization of passenger processes
  Security lines
  Migration controls
  Airplane taxiways
  Runway capacity
  Air traffic flow (TSO)
Ease with which students learn simulation
  Version 10 is a great improvment!!! Students program and construct their own modules and interfaces. The documentation is very inuitive. I use it sometimes instead of my lecture slides.
Benefits attained through the use of ExtendSim
  At the beginning, I used ARENA and Simulink but Extendsim is more intuitive and I see better results in seminar works and exams. (Important: I don't say that because of this questionaire!)
Will you be using ExtendSim in future courses?
  Yes. I will use in courses like Traffic System Operation (Bachelor Aviation course) and Simulation (Module in a Masters course for Aviation Master students).
Anything else you would like to add?
  Due to the use of Extendsim in my course, Beeing/Aurora Aerospace and Laser Enterprise bought a licence. Swiss Post will follow soon!