An ant-based heuristic for the railway traveling salesman problem

被引:0
|
作者
Pop, Petrica C. [1 ]
Pintea, Camelia M. [2 ]
Sitar, Corina Pop [3 ]
机构
[1] North Univ Baia Mare, Fac Sci, Dept Math & Comp Sci, Baia Mare, Romania
[2] Univ Babes Bolyai, Fac Math & Comp Sci, Cluj Napoca, Romania
[3] Univ Babes Bolyai, Fac Econ, Cluj Napoca, Romania
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We consider the Railway Raveling Salesman Problem, denoted RTSP, in which a salesman using the railway network wishes to visit a certain number of cities to carry out his/her business, starting and ending at the same city, and having the goal to minimize the overall time of the journey. The RTSP is NP-hard and it is related to the Generalized Traveling Salesman Problem. In this paper we present an effective meta-heuristic based on ant colony optimization (ACO) for solving the RTSP. Computational results are reported for real-world and synthetic data. The results obtained demonstrate the superiority of the proposed algorithm in comparison with the existing method.
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页码:702 / +
页数:2
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