Application of Genetic Algorithm on Travelling Salesman Person

Sambourou Massinanke; Chao Zhu Zhang

doi:10.4028/www.scientific.net/AMR.1048.526

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 1048Application of Genetic Algorithm on Travelling...

Application of Genetic Algorithm on Travelling Salesman Person

Abstract:

GA (Genetic algorithm) is an optimization method based on operators (mutation and crossover) utilizing a survival of the fittest idea. They are utilized favorably in various problems. (TSP) Travelling salesman problem is one of the famous studied. TSP is a permutation problem in which the aim is to determine the shortest tour between n different points (cities), otherwise, the problem aims to find a route covering all cities where that the total distance is minimal. In this study a single salesman travels to each of the cities and close the loop by returning to the city he started, the aim of this study is to determine the minimum number of generations in which salesman does the minimum path, cities are chosen at random as initial population. The new generations are then created iteratively till the proper path is attained.

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Periodical:

Advanced Materials Research (Volume 1048)

Pages:

526-530

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.1048.526

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Online since:

October 2014

Authors:

Sambourou Massinanke*, Chao Zhu Zhang

Keywords:

Genetic Algorithm (GA), Partially Matched Crossover, Population, Traveler Salesman Problem

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References

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