This paper addresses the design of large-scale, integrated sites considering random process failures. Using a novel mixed-integer linear programming (MILP) model, the authors are able to maximize the average production capacity of an integrated site while minimizing the required capital investment. In this case study, ExtendSim is used to analyze a scenario reduction technique, reporting the results of simulating the operation of the Pareto-optimal designs.
An Efficient Method for Optimal Design of Large-Scale Integrated Chemical Production Sites with Endogenous Uncertainty
