Improving the Solution of Traveling Salesman Problem Using Genetic, Memetic Algorithm and Edge assembly Crossover

被引：0

作者：

Haque, Mohd. Junedul ^{[1
]}

Magld, Khalid. W. ^{[2
]}

机构：

[1] Taif Univ, Coll Comp & Info Technol, At Taif, Saudi Arabia

[2] King Abdulaziz Univ, Fac Comp & IT, Coll Comp & Info Tech, At Taif, Saudi Arabia

来源：

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS | 2012年 / 3卷 / 07期

关键词：

NP Hard; GA(Genetic algorithms); TSP(Traveling salesman problem); MA(Memetic algorithms); EAX(Edge Assembly Crossover);

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The Traveling salesman problem (TSP) is to find a tour of a given number of cities (visiting each city exactly once) where the length of this tour is minimized. Testing every possibility for an N city tour would be N! Math additions. Genetic algorithms (GA) and Memetic algorithms (MA) are a relatively new optimization technique which can be applied to various problems, including those that are NPhard. The technique does not ensure an optimal solution, however it usually gives good approximations in a reasonable amount of time. They, therefore, would be good algorithms to try on the traveling salesman problem, one of the most famous NP-hard problems. In this paper I have proposed a algorithm to solve TSP using Genetic algorithms (GA) and Memetic algorithms (MA) with the crossover operator Edge Assembly Crossover (EAX) and also analyzed the result on different parameter like group size and mutation percentage and compared the result with other solutions.

引用

页码：108 / 111

页数：4

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