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Intelligent modeling method based on genetic algorithm for partner selection in virtual organizations

Author

Listed:
  • Dinu Simona

    (Faculty of Naval Electromechanics, Constanta Maritime University, Romania)

  • Pacuraru Raluca

    (Faculty of Accounting and Financial Management, Constanta “Spiru Haret” University, Romania)

Abstract

The goal of a Virtual Organization is to find the most appropriate partners in terms of expertise, cost wise, quick response, and environment. In this study we propose a model and a solution approach to a partner selection problem considering three main evaluation criteria: cost, time and risk. This multiobjective problem is solved by an improved GA that includes meiosis specific characteristics and step-size adaptation for the mutation operator. The algorithm performs strong exploration initially and exploitation in later generations. It has high global search ability and a fast convergence rate and also avoids premature convergence. On the basis of the numerical investigations, the incorporation of the proposed enhancements has been successfully proved.

Suggested Citation

  • Dinu Simona & Pacuraru Raluca, 2011. "Intelligent modeling method based on genetic algorithm for partner selection in virtual organizations," Business and Economic Horizons (BEH), Prague Development Center, vol. 5(2), pages 23-34, April.
    • Handle: RePEc:pdc:jrnbeh:v:5:y:2011:i:2:p:23-34
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    References listed on IDEAS

    as
    1. Ip, W. H. & Yung, K. L. & Wang, Dingwei, 2004. "A branch and bound algorithm for sub-contractor selection in agile manufacturing environment," International Journal of Production Economics, Elsevier, vol. 87(2), pages 195-205, January.
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    4. Famuyiwa, Oluwafemi & Monplaisir, Leslie & Nepal, Bimal, 2008. "An integrated fuzzy-goal-programming-based framework for selecting suppliers in strategic alliance formation," International Journal of Production Economics, Elsevier, vol. 113(2), pages 862-875, June.
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    More about this item

    Keywords

    Virtual organization; partner selection; optimization; genetic algorithm;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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