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Mutual benefits of two multicriteria analysis methodologies: A case study for batch plant design

Azzaro-Pantel, Catherine and Zaraté, Pascale Mutual benefits of two multicriteria analysis methodologies: A case study for batch plant design. (2009) Engineering Applications of Artificial Intelligence, 22 (4-5). 546-556. ISSN 0952-1976

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Official URL: http://doi.org/10.1016/j.engappai.2009.02.008


This paper presents a MultiObjective Genetic Algorithm (MOGA) optimization framework for batch plant design. For this purpose, two approaches are implemented and compared with respect to three criteria, i.e., investment cost, equipment number and a flexibility indicator based on work in process (the so-called WIP) computed by use of a discrete-event simulation model. The first approach involves a genetic algorithm in order to generate acceptable solutions, from which the best ones are chosen by using a Pareto Sort algorithm. The second approach combines the previous Genetic Algorithm with a multicriteria analysis methodology, i.e., the Electre method in order to find the best solutions. The performances of the two procedures are studied for a large-size problem and a comparison between the procedures is then made.

Item Type:Article
Additional Information:Thanks to Elsevier editor.The definitive version is available at http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V2M-4W68DVR-1&_user=1072870&_coverDate=06%2F30%2F2009&_alid=962278177&_rdoc=1&_fmt=high&_orig=search&_cdi=5706&_sort=r&_docanchor=&view=c&_ct=11&_acct=C000043979&_version=1&_urlVersion=0&_userid=1072870&md5=a5f68fc3600563bfa0d8fb3b1f5d9a94
HAL Id:hal-03573106
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
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Deposited On:20 Jul 2009 09:27

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