Integrating environmental impact minimization into batch plant design: Aepplication to protein production

This work deals with the multi-criteria cost-environment design of multi-product batch plants, where the design variables are the equipment items' size as well as the operating conditions. The case study is a multi-product batch plant for the production of four recombinant proteins. Given the important combinatorial aspect of the problem, the approach used consists in coupling a stochastic algorithm.. indeed a Genetic Algorithm (GA) with a Discrete Event Simulator (DES). For this purpose, a Multi-criteria Genetic Algorithm (MUGA) was developed with a Pareto optimal ranking method. The results show how the methodology can be used to find a range of trade-off solutions for optimizing batch plant design.