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題名 Ant Colony Optimization- Based Algorithm for Airline Crew Scheduling Problem
作者 林我聰
Deng, Guang-Feng; Lin, Woo-Tsong
貢獻者 資管系
關鍵詞 Ant colony optimization (ACO); Airline crew scheduling; Swarm intelligence; Combinatorial optimization problem
日期 2011-05
上傳時間 18-二月-2014 15:17:53 (UTC+8)
摘要 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.
關聯 Expert Systems with Applications, 38(5), 5787-5793
資料類型 article
DOI http://dx.doi.org/10.1016/j.eswa.2010.10.053
dc.contributor 資管系en_US
dc.creator (作者) 林我聰zh_TW
dc.creator (作者) Deng, Guang-Feng; Lin, Woo-Tsongen_US
dc.date (日期) 2011-05en_US
dc.date.accessioned 18-二月-2014 15:17:53 (UTC+8)-
dc.date.available 18-二月-2014 15:17:53 (UTC+8)-
dc.date.issued (上傳時間) 18-二月-2014 15:17:53 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/63947-
dc.description.abstract (摘要) 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.en_US
dc.format.extent 324047 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Expert Systems with Applications, 38(5), 5787-5793en_US
dc.subject (關鍵詞) Ant colony optimization (ACO); Airline crew scheduling; Swarm intelligence; Combinatorial optimization problemen_US
dc.title (題名) Ant Colony Optimization- Based Algorithm for Airline Crew Scheduling Problemen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.eswa.2010.10.053-
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.eswa.2010.10.053-