A hybrid particle swarm optimization model for the traveling salesman problem

被引：11

作者：

Machado, TR ^{[1
]}

Lopes, HS ^{[1
]}

机构：

[1] Fed Ctr Technol Educ Parana, CPGEI, Bioinformat Lab, Curitiba, Parana, Brazil

来源：

ADAPTIVE AND NATURAL COMPUTING ALGORITHMS | 2005年

关键词：

D O I：

10.1007/3-211-27389-1_61

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work presents a new hybrid model, based on Particle Swarm Optimization, Genetic Algorithms and Fast Local Search, for the symmetric blind traveling salesman problem. A detailed description of the model is provided. The implemented system was tested with instances from 76 to 2103 cities. For instances up to 439 cities, results were, in average, less than or around 1% in excess of the known optima. When considering all instances, results were 2.1498% in excess, in average. These excellent results encourage further research and improvement of the hybrid model.

引用

页码：255 / 258

页数：4

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