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New Population initialization and sequential transformation methods of Genetic Algorithms for solving optimal TSP problem  

Kang, Rae-Goo (조선대학교 전산통계학과)
Lim, Hee-Kyoung (조선대학교 전산통계학과)
Jung, Chai-Yeoung (조선대학교 전산통계학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.10, no.3, 2006 , pp. 622-627 More about this Journal
Abstract
TSP(Traveling Salesman Problem) is a problem finding out the shortest distance out of many courses where given cities of the number of N, one starts a certain city and turns back to a starting city, visiting every city only once. As the number of cities having visited increases, the calculation rate increases geometrically. This problem makes TSP classified in NP-Hard Problem and genetic algorithm is used representatively. To obtain a better result in TSP, various operators have been developed and studied. This paper suggests new method of population initialization and of sequential transformation, and then proves the improvement of capability by comparing them with existing methods.
Keywords
TSP; Traveling Salesman Problem;
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