A MultiObjective Genetic Algorithm Optimization Framework for Batch Plant Design


This paper presents a MultiObjective Genetic Algorithm (MOGA) optimization framework for batch plant design. For this purpose, two MOGAs are implemented with respect to three criteria, i.e., investment cost, equipment number and a flexibility indicator based on Work In Process (the so-called WIP) computed by use of a Discrete-Event simulation model. The performances of the two procedures are studied for a large-size problem.