GLS Optimization Algorithm for Solving Travelling Salesman Problem

被引：2

作者：

Neissi, Nourolhoda Alemi ^{[1
]}

Mazloom, Masoud ^{[2
]}

机构：

[1] Khouzestan Reg Elect Co, Off Stand & Res, Ahvaz, Iran

[2] Shahid Chamran Univ, Fac Engn, Dept Comp Engn, Ahvaz, Iran

来源：

SECOND INTERNATIONAL CONFERENCE ON COMPUTER AND ELECTRICAL ENGINEERING, VOL 1, PROCEEDINGS | 2009年

关键词：

component; Combinatorial Optimization; Genetic Algorithm; Local Search; Genetic Local Search; Metaheuristic; Travelling salesman problem;

D O I：

10.1109/ICCEE.2009.102

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Travelling salesman problem (TSP) is well known as one of the combinatorial optimization problems. There are many approaches for finding solution to the TSP. In this paper we used combination of local search heuristics and genetic algorithm (GLS) that has been shown to be an efficient algorithm for finding near optimal to the TSP. We also evaluate the run time behavior and fitness of our approach and compare it with other methods. A reasonable result is obtained and the proposed algorithm is able to get to a better solution in less time.

引用

页码：291 / +

页数：3

共 13 条

[1] Metaheuristics in combinatorial optimization: Overview and conceptual comparison [J].

Blum, C ;

Roli, A .

ACM COMPUTING SURVEYS, 2003, 35 (03) :268-308

[2]

BONYADI M, 2008, POPULATION BASED OPT, P1

[3]

Eiben G, 2008, NAT COMPUT SER, P153, DOI 10.1007/978-3-540-72960-0_8

[4]

Gen M., 1999, Genetic Algorithms and Engineering Optimization

[5]

Golberg DE., 1989, Choice Reviews Online, V1989, P36, DOI DOI 10.5860/CHOICE.27-0936

[6]

HANSEN MP, 2000, J HEURISTIC IN PRESS

[7]

Haupt R., 2004, Practical Genetic Algorithms, V2nd ed

[8]

Holland J., 1975, Adaptation in Natural and Artificial Systems, DOI 10.7551/mitpress/1090.001.0001

[9]

MERZ P, 1997, IEEE INT C EV COMP

[10]

MOSCATO P, 1989, 826 CALT CONC COM PR

← 1 2 →