A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization

Hongwei Ding; Lyès Benyoucef; Xiaolan Xie

emse-00449373, version 1

A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization

Hongwei Ding ¹, Lyès Benyoucef ¹, Xiaolan Xie () ^2, 3, 4

Engineering Applications of Artificial Intelligence 19, 6 (2006) 609-623

Résumé : Nowadays, in a hotly competitive environment, companies are continuously trying to provide products and/or services to customers faster, cheaper, and better than the competitors do. Managers have learned that they cannot do it alone; rather, they must work on a cooperative basis with other organizations in order to succeed. Although the resulting enterprise networks are more competitive, the tasks for planning, management and optimization are much more difficult and complex. In this paper, we present a newly developed toolbox "ONE" to support decision makers for the assessment, design and improvement of such supply chain networks. The toolbox comprises innovative and user-friendly concepts related to the modeling, simulation and optimization of modern enterprise networks. Two case studies, proposed by partners from automotive and textile industries, are presented and computational results analysed.

1 : MACSI (INRIA Lorraine - LORIA)
INRIA – CNRS : UMR7503 – Université Henri Poincaré - Nancy I – Université Nancy II – Ecole normale supérieure de Paris - ENS Paris – Institut National Polytechnique de Lorraine (INPL)
2 : Centre Ingénierie et Santé (CIS-ENSMSE)
École Nationale Supérieure des Mines - Saint-Étienne
3 : Département Génie Industriel Hospitalier (GIH-ENSMSE)
École Nationale Supérieure des Mines - Saint-Étienne – CIS
4 : Institut Fédératif de Recherche en Sciences et Ingénierie de la Santé (IFRESIS-ENSMSE)
École Nationale Supérieure des Mines - Saint-Étienne – IFR143

Collaboration : INRIA-LORRAINE

emse-00449373, version 1
http://hal-emse.ccsd.cnrs.fr/emse-00449373
oai:hal-emse.ccsd.cnrs.fr:emse-00449373
Contributeur : Andrée-Aimée Toucas <>
Soumis le : Jeudi 21 Janvier 2010, 14:23:55
Dernière modification le : Vendredi 1 Avril 2011, 15:10:49

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DOI : 10.1016/j.engappai.2005.12.008

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%% emse-00449373, version 1
%% http://hal-emse.ccsd.cnrs.fr/emse-00449373
@article{ding:emse-00449373,
    hal_id = {emse-00449373},
    url = {http://hal-emse.ccsd.cnrs.fr/emse-00449373},
    title = {{A simulation-based multi-objective genetic algorithm approach for networked enterprises optimization}},
    author = {Ding, Hongwei and Benyoucef, Ly{\`e}s and Xie, Xiaolan},
    abstract = {{Nowadays, in a hotly competitive environment, companies are continuously trying to provide products and/or services to customers faster, cheaper, and better than the competitors do. Managers have learned that they cannot do it alone; rather, they must work on a cooperative basis with other organizations in order to succeed. Although the resulting enterprise networks are more competitive, the tasks for planning, management and optimization are much more difficult and complex. In this paper, we present a newly developed toolbox "ONE" to support decision makers for the assessment, design and improvement of such supply chain networks. The toolbox comprises innovative and user-friendly concepts related to the modeling, simulation and optimization of modern enterprise networks. Two case studies, proposed by partners from automotive and textile industries, are presented and computational results analysed.}},
    keywords = {Networked enterprise; simulation; optimization},
    language = {Anglais},
    affiliation = {MACSI - INRIA Lorraine - LORIA , Centre Ing{\'e}nierie et Sant{\'e} - CIS-ENSMSE , D{\'e}partement G{\'e}nie Industriel Hospitalier - GIH-ENSMSE , Institut F{\'e}d{\'e}ratif de Recherche en Sciences et Ing{\'e}nierie de la Sant{\'e} - IFRESIS-ENSMSE},
    pages = {609-623},
    journal = {Engineering Applications of Artificial Intelligence},
    volume = {19},
    number = {6 },
    note = {Fichier PDF : XX-EAAI-19-6 Fichier PDF : XX-EAAI-19-6 },
    audience = {internationale },
    collaboration = {INRIA-LORRAINE },
    doi = {10.1016/j.engappai.2005.12.008 },
    year = {2006},
}

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