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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/76519

Title:	Using ant colony optimization algorithm to solve airline crew scheduling problems
Authors:	Lo, C.-C.;Deng, Guang-Feng 鄧廣豐
Contributors:	資管系
Keywords:	Airline crew scheduling problems;Near-optimal solutions;Air transportation;Combinatorial optimization;Problem solving;Scheduling;Traveling salesman problem;Learning algorithms
Date:	2007
Issue Date:	2015-07-13 16:29:17 (UTC+8)
Abstract:	In this paper, an Ant Colony Optimization (ACO) based Ant Crew Scheduling Model (ACSM) is proposed to solve airline crew scheduling problems. In the proposed ACSM, airline crew scheduling problems are first formulated as traveling salesman problems with flight graph representation. Then, the ACO algorithm is applied to search near-optimal solutions for airline crew schedules. The validity of the proposed ACSM is verified by implementing it in real study cases. The results from the implementation and evaluation confirm that the proposed ACSM is suitable for the airline crew scheduling problems with good performance. © 2007 IEEE.
Relation:	Proceedings - Third International Conference on Natural Computation, ICNC 2007,Volume 4, 論文編號 4344781, Pages 797-801 3rd International Conference on Natural Computation, ICNC 2007,24 August 2007 through 27 August 2007,Haikou, Hainan
Data Type:	conference
DOI 連結:	http://dx.doi.org/10.1109/ICNC.2007.797
DOI:	10.1109/ICNC.2007.797
Appears in Collections:	[資訊管理學系] 會議論文

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