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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/63947
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/63947

    Title: Ant Colony Optimization- Based Algorithm for Airline Crew Scheduling Problem
    Authors: 林我聰
    Deng, Guang-Feng;Lin, Woo-Tsong
    Contributors: 資管系
    Keywords: Ant colony optimization (ACO);Airline crew scheduling;Swarm intelligence;Combinatorial optimization problem
    Date: 2011-05
    Issue Date: 2014-02-18 15:17:53 (UTC+8)
    Abstract: Airline crew scheduling is an NP-hard constrained combinatorial optimization problem, and an effective crew scheduling system is essential for reducing operating costs in the airline industry. Ant colony optimization algorithm (ACO) has successfully applied to solve many difficult and classical optimization problems especially on traveling salesman problems (TSP). Therefore, this paper formulated airline crew scheduling problem as Traveling Salesman Problem and then introduce ant colony optimization algorithm to solve it. Performance was evaluated by performing computational tests regarding real cases as the test problems. The results showed that ACO-based algorithm can be potential technique for airline crew scheduling.
    Relation: Expert Systems with Applications, 38(5), 5787-5793
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.eswa.2010.10.053
    DOI: 10.1016/j.eswa.2010.10.053
    Appears in Collections:[資訊管理學系] 期刊論文

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