Discrete cuckoo search algorithm for the travelling salesman problem

被引:289
|
作者
Ouaarab, Aziz [1 ]
Ahiod, Belaid [1 ]
Yang, Xin-She [2 ]
机构
[1] Mohammed V Agdal Univ, Associated Unit, LRIT, CNRST URAC 29, Rabat, Morocco
[2] Middlesex Univ, Sch Sci & Technol, London NW4 4BT, England
来源
NEURAL COMPUTING & APPLICATIONS | 2014年 / 24卷 / 7-8期
关键词
Nature-inspired metaheuristics; Cuckoo search; Levy flights; Combinatorial optimisation; Traveling salesman problem; PARTICLE SWARM OPTIMIZATION;
D O I
10.1007/s00521-013-1402-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present an improved and discrete version of the Cuckoo Search (CS) algorithm to solve the famous traveling salesman problem (TSP), an NP-hard combinatorial optimisation problem. CS is a metaheuristic search algorithm which was recently developed by Xin-She Yang and Suash Deb in 2009, inspired by the breeding behaviour of cuckoos. This new algorithm has proved to be very effective in solving continuous optimisation problems. We now extend and improve CS by reconstructing its population and introducing a new category of cuckoos so that it can solve combinatorial problems as well as continuous problems. The performance of the proposed discrete cuckoo search (DCS) is tested against a set of benchmarks of symmetric TSP from the well-known TSPLIB library. The results of the tests show that DCS is superior to some other metaheuristics.
引用
收藏
页码:1659 / 1669
页数:11
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