Ecodesign of Batch Processes: Optimal Design Strategies for Economic and Ecological Bioprocesses

Adrian Dietz (1) , Catherine Azzaro-Pantel (2) , Luc Pibouleau (2) , Serge Domenech (2)

1 LSGC - Laboratoire des Sciences du Génie Chimique
2 LGC - Laboratoire de Génie Chimique

This work deals with the multicriteria cost-environment design of multiproduct batch plants, where the design variables are the equipment item sizes as well as the operating conditions. The case study is a multiproduct 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). To take into account the conflicting situations that may be encountered at the earliest stage of batch plant design, i.e. compromise situations between cost and environmental consideration, a Multicriteria 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.

Mots clés: Multicriteria optimization; Genetic algorithm; Batch plant design; Environmental impact

Domaines: Génie chimique

Adrian Dietz, Catherine Azzaro-Pantel, Luc Pibouleau, Serge Domenech. Ecodesign of Batch Processes: Optimal Design Strategies for Economic and Ecological Bioprocesses. International Journal of Chemical Reactor Engineering, 2007, 5, pp.0. ⟨hal-03594247⟩