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Genetic algorithms for the scheduling of multiproduct batch plants within uncertain environment

Azzaro-Pantel, Catherine and Bonfill, Anna and Domenech, Serge and Pibouleau, Luc and Ponsich, Antonin Genetic algorithms for the scheduling of multiproduct batch plants within uncertain environment. (2007) Computer Aided Chemical Engineering, 24. 619-624. ISSN 1570-7946

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Official URL: http://dx.doi.org/10.1016/S1570-7946(07)80126-X


This study addresses the problem of batch plant scheduling. In addition uncertainty on product demands is considered through probabilistic-based methods. In the resulting two-stage stochastic programming problem, the objective is to maximize an Expected Profit Value (EPV) while respecting a constraint forcing the makespan to be lower than a time horizon. A Genetic Algorithm (GA) is proposed for the solution of a multiproduct example. The variable encoding requires special attention. Computational tests are first carried out with a deterministic model to validate the GA efficiency. Then, different runs with different scenario sets highlight the existence of various solution classes, characterized by specific numbers of batches manufactured for each product. Further analysis finally enables to discuss if each schedule is really the best-fitted to the scenario set for which it has been determined.

Item Type:Article
Additional Information:Escape 17 : http://www.escape17.upb.ro/index.htm
HAL Id:hal-03592092
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 > Universitat Politècnica de Catalunya - UPC (SPAIN)
Laboratory name:
Laboratoire de Génie Chimique - LGC (Toulouse, France) - Procédés Systèmes Industriels (PSI)
Deposited On:17 Jul 2009 10:31

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