Teaching mathematical modeling software for multiobjective optimization in chemical engineering courses

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Title: Teaching mathematical modeling software for multiobjective optimization in chemical engineering courses
Authors: García, Norberto | Ruiz-Femenia, Rubén | Caballero, José A.
Research Group/s: Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT)
Center, Department or Service: Universidad de Alicante. Departamento de Ingeniería Química
Keywords: Multiobjective optimization | Chemical process design | Post-secondary education | Economic and environmental assessment | The ɛ-constraint method
Knowledge Area: Ingeniería Química
Issue Date: Dec-2012
Publisher: Elsevier
Citation: Education for Chemical Engineers. 2012, 7(4): e169-e180. doi:10.1016/j.ece.2012.07.001
Abstract: This paper expects to give undergraduate students some guidelines about how to incorporate environmental considerations in a chemical supply chain and how the introduction of these concerns have an important effect on the results obtained in the multiobjective optimization problem where both economic and environmental aspects are considered simultaneously. To extend the economic and environmental assessment outside the chemical plant and to identify the tradeoffs associated with the reality of chemical and petrochemical industries, a simplified problem of a chemical supply chain is proposed as a case study. The inclusion of environmental concerns to this economic problem make this new case study a good example for undergraduate students interested in implementing simultaneous economic and environmental considerations in the chemical process design incorporating mathematical modeling software for solving this multiobjective problem. Thus, the final objective of this paper is to show to undergraduate students how environmental together with economic considerations could have an important impact in the logistics of a supply chain and how multiobjective optimization could be used to make better decisions in the design of chemical processes including its supply chain. To reach our purpose, the Pareto curve of the supply chain is obtained using the ɛ-constraint method. In addition, the tradeoffs of this multiobjective optimization have been identified and analyzed and ultimately a good decision based on the set of ‘equivalent’ optimal solutions for this chemical supply chain problem determined.
Sponsor: Spanish Ministry of Education and Science (CTQ2009-14420).
URI: http://hdl.handle.net/10045/75113
ISSN: 1749-7728
DOI: 10.1016/j.ece.2012.07.001
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2012 The Institution of Chemical Engineers. Published by Elsevier B.V.
Peer Review: si
Publisher version: https://doi.org/10.1016/j.ece.2012.07.001
Appears in Collections:INV - CONCEPT - Artículos de Revistas

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