淡江大學機構典藏:Item 987654321/69158
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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/69158


    Title: A two-stage genetic algorithm for solving the transportation problem with fuzzy demands and fuzzy supplies
    Authors: Lin, Feng-Tse;Tsai, Tzong-Ru
    Contributors: 淡江大學統計學系
    Keywords: Genetic algorithms;Fuzzy transportation problem;Fuzzy demand;Fuzzy supply
    Date: 2009-12
    Issue Date: 2011-10-23 16:26:40 (UTC+8)
    Publisher: Kumamoto: ICIC International
    Abstract: This paper investigates solving the transportation problem with fuzzy demands and fuzzy supplies using a two-stage genetic algorithm (GA). At the first stage, we simulate a fuzzy number by distributing a fuzzy value into certain partition points. We then use GA to evolve the values in each partition point and the final values represent the membership grade of that fuzzy number. As a result, we obtain the estimated values of all fuzzy demands and fuzzy supplies and the original fuzzy problem becomes a defuzzified instance. The best solution to the defuzzified instance is then solved by the following stage via evolution process. The experimental results show that the proposed two-stage GA approach outperforms the other fuzzy approach to solving the transportation problem with fuzzy demands and fuzzy supplies.
    Relation: International Journal of Innovative Computing, Information and Control 5(12)pt.B, pp.4775-4785
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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