Ecodesign of Chemical Processes with Multi-Objective Genetic Algorithms


Process synthesis is a complex activity that has long been identified as a main issue in the process systems engineering community. This involves many decision makers and multiple levels of decision steps. From these many potential alternatives, the designers want to select the one that best suits both economic and environmental criteria. The objective of this chapter is to show that multi-objective optimization and multiple choice decision making (MCDM) techniques can be useful to facilitate the ecodesign of a process. Two examples illustrate the determination of eco-friendly and cost-effective designs: the Williams and Otto plant and the benchmark HDA process for hydrodealkylation of toluene to produce benzene, are analyzed through a multi-objective optimization approach. This chapter deals with the definition of various objectives for designing eco-efficient processes, by considering ecological and economic features simultaneously. The environmental issue at the grass-root design of chemical processes is quantified according to a set of metrics or indicators following the guidelines of sustainability concepts proposed by IChemE. An improved variant of the well known NSGA-II is implemented for solving the resulting multi-objective problems. The environmental burdens are evaluated by means of the package ARIANE™, a decision-support tool dedicated to the management of plant utilities (steam, electricity, hot water, and so forth) and to the emission control of pollutants (CO2, SO2, NO, and so forth). The implementation of ARIANE™, to compute the primary energy requirements of the process and to quantify its pollutant emissions, constitutes a key point of the approach. The optimization procedure provides a set of compromise solutions; a MCDM procedure is then used to find the most interesting tradeoff design alternatives.