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

Abstract

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.

Optimization of Recovery Processes for Multiple Economic and Environmental Objectives

“…An example of environmental metric computation is as follows. Dietz et al [25][26][27] measured the environmental impact of multiproduct batch plants based on the amount of wastes/ pollutants generated per unit of production (see eq 1). The calculations require the use of emission factors (I i k ), each of which is defined as the amount of pollutant i produced per unit of product k. The pollutants considered in the problem are solvent and biomass.…”