Multiobjective evolutionary optimization of batch process scheduling under environmental and economic concerns

• Published in: AIChE journal Vol. 59; no. 2; pp. 429 - 444
• Main Authors: Capón-García, Elisabet, Bojarski, Aarón D., Espuña, Antonio, Puigjaner, Luis
• Format: Journal Article Publication
• Language: English
• Published: New York Blackwell Publishing Ltd 01.02.2013; American Institute of Chemical Engineers
• Subjects: Aparells i instruments; Aspectes econòmics; Batch production; Chemical engineering; Data processing; Economics; Enginyeria química; Environmental objective; Evolutionary; Evolutionary algorithms; Genetic algorithms; Indústria dels processos químics; LCA; Multiobjective optimization; Multiproduct batch scheduling; Optimization; Optimization techniques; Plant chemical ecology; Plantes químiques; Product changeover; Production scheduling; Scheduling; Sequence dependency; Stands; Strategy; Tradeoffs; Àrees temàtiques de la UPC
• ISSN: 0001-1541; 1547-5905
• DOI: 10.1002/aic.13841

The simultaneous consideration of economic and environmental objectives in batch production scheduling is today a subject of major concern. However, it constitutes a complex problem whose solution necessarily entails production trade‐offs. Unfortunately, a rigorous multiobjective optimization approach to solve this kind of problem often implies high computational effort and time, which seriously undermine its applicability to day‐to‐day operation in industrial practice. Hence, this work presents a hybrid optimization strategy based on rigorous local search and genetic algorithm to efficiently deal with industrial scale batch scheduling problems. Thus, a deeper insight into the combined environmental and economic issues when considering the trade‐offs of adopting a particular schedule is provided. The proposed methodology is applied to a case study concerning a multiproduct acrylic fiber production plant, where product changeovers influence the problem results. The proposed strategy stands for a marked improvement in effectively incorporating multiobjective optimization in short‐term plant operation. © 2012 American Institute of Chemical Engineers AIChE J, 59: 429–444, 2013