| 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-Tsong | en_US |
| dc.date (日期) | 2011-05 | en_US |
| dc.date.accessioned | 18-Feb-2014 15:17:53 (UTC+8) | - |
| dc.date.available | 18-Feb-2014 15:17:53 (UTC+8) | - |
| dc.date.issued (上傳時間) | 18-Feb-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), 5787-5793 | en_US |
| dc.subject (關鍵詞) | Ant colony optimization (ACO); Airline crew scheduling; Swarm intelligence; Combinatorial optimization problem | en_US |
| dc.title (題名) | Ant Colony Optimization- Based Algorithm for Airline Crew Scheduling Problem | en_US |
| dc.type (資料類型) | article | en |
| 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 | - |
