Advanced intelligent technique of real genetic algorithm for Traveling Salesman Problem optimization

被引：0

作者：

Awad, A. R. ^{[1
]}

Von Poser, I. ^{[2
]}

Aboul-Ela, M. T. ^{[3
]}

机构：

[1] Tishreen Univ, Dept Environm Engn, Latakia, Syria

[2] Merck KGaA, Darmstadt, Germany

[3] Menia Univ, Dept Civil Engn, Al Minya, Egypt

来源：

PROCEEDINGS OF THE 9TH WSEAS INTERNATIONAL CONFERENCE ON MATHEMATICAL AND COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING (MACMESE '07)/ DNCOCO '07 | 2007年

关键词：

intelligent technique; real genetic algorithms; optimization; traveling salesman problem; large-scale example;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work aims at solving the Traveling Salesman Problem (TSP) through developing an advanced intelligent technique based on real genetic algorithm (GA). The used GA comprises real-value coding with specific behavior taking each code as it is (whether binary, integer, or real), rank selection, and efficient uniform genetic operators. The results indicated, in comparison with the other applied optimization methods (linear, dynamic, Monte Carlo and heuristic search methods), that the real GA produces significantly the lowest distance (least cost tour) solution. It is concluded that real GA approach is robust and it represents an efficient search method and is easily applied to nonlinear and complex problems of the TSP in the field of solid waste routing system in the large cities.

引用

页码：447 / 453

页数：7

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