A discrete invasive weed optimization algorithm for solving traveling salesman problem

被引:94
|
作者
Zhou, Yongquan [1 ,2 ]
Luo, Qifang [1 ]
Chen, Huan [1 ]
He, Anping [1 ,2 ]
Wu, Jinzhao [1 ,2 ]
机构
[1] Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Peoples R China
[2] Guangxi Key Lab Hybrid Computat & IC Design Anal, Nanning 530006, Peoples R China
基金
美国国家科学基金会;
关键词
Discrete invasive weed optimization; Positive integer encode; 3-Opt; I2Opt; TSP; PROBABILISTIC NEURAL-NETWORKS;
D O I
10.1016/j.neucom.2014.01.078
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Traveling Salesman Problem (TSP) is one of the typical NP-hard problems. Efficient algorithms for the TSP have been the focus on academic circles at all times. This article proposes a discrete invasive weed optimization (DIWO) to solve TSP. Firstly, weeds individuals encode positive integer, on the basis that the normal distribution of the IWO does not change, and then calculate the fitness value of the weeds individuals. Secondly, the 3-Opt local search operator is used. Finally, an improved complete 2-Opt (I2Opt) is selected as a second local search operator for solve TSP. A benchmarks problem selected from TSPLIB is used to test the algorithm, and the results show that the DIWO algorithm proposed in this article can achieve to results closed to the theoretical optimal values within a reasonable period of time, and has strong robustness. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:1227 / 1236
页数:10
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