OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design

Aguilar-Lasserre, Alberto and Pibouleau, Luc and Azzaro-Pantel, Catherine and Domenech, Serge Enhanced genetic algorithm-based fuzzy multiobjective strategy to multiproduct batch plant design. (2009) Applied Soft Computing, 9 (4). 1321-1330. ISSN 1568-4946

(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader

Official URL: http://dx.doi.org/10.1016/j.asoc.2009.05.005


This paper addresses the problem of the optimal design of batch plants with imprecise demands in product amounts. The design of such plants necessary involves how equipment may be utilized, which means that plant scheduling and production must constitute a basic part of the design problem. Rather than resorting to a traditional probabilistic approach for modeling the imprecision on product demands, this work proposes an alternative treatment by using fuzzy concepts. The design problem is tackled by introducing a new approach based on a multiobjective genetic algorithm, combined wit the fuzzy set theory for computing the objectives as fuzzy quantities. The problem takes into account simultaneous maximization of the fuzzy net present value and of two other performance criteria, i.e. the production delay/advance and a flexibility index. The delay/advance objective is computed by comparing the fuzzy production time for the products to a given fuzzy time horizon, and the flexibility index represents the additional fuzzy production that the plant would be able to produce. The multiobjective optimization provides the Pareto's front which is a set of scenarios that are helpful for guiding the decision's maker in its final choices. About the solution procedure, a genetic algorithm was implemented since it is particularly well-suited to take into account the arithmetic of fuzzy numbers. Furthermore because a genetic algorithm is working on populations of potential solutions, this type of procedure is well adapted for multiobjective optimization.

Item Type:Article
Additional Information:Thanks to Elsevier editor. The definitive version is available at http://www.sciencedirect.com/science/article/pii/S1568494609000647
HAL Id:hal-03563451
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Other partners > Instituto Tecnologico de Orizaba (MEXICO)
Laboratory name:
Laboratoire de Génie Chimique - LGC (Toulouse, France) - Procédés Systèmes Industriels (PSI) - Conception Optimisation Ordonnancement des Procédés (COOP)
Deposited On:28 Oct 2011 10:13

Repository Staff Only: item control page