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Subtour Preservation Crossover Operator for the Symmetric TSP  

Soak, Sang-Moon (Information Systems Examination Team, Korean Intellectual Property Office)
Lee, Hong-Girl (Division of e-business, Kyungnam University)
Byun, Sung-Cheal (Information Systems Examination Team, Korean Intellectual Property Office)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.33, no.2, 2007 , pp. 201-212 More about this Journal
Abstract
Genetic algorithms (GAs) are very useful methods for global search and have been applied to various optimization problems. They have two kinds of important search mechanisms, crossover and mutation. Because the performance of GAs depends on these operators, a large number of operators have been developed for improving the performance of GAs. Especially, many researchers have been more interested in a crossover operator than a mutation operator. The reason is that a crossover operator is a main search operator in GAs and it has a more effect on the search performance. So, we also focus on a crossover operator. In this paper we first investigate the drawback of various crossovers, especially subtour-based crossovers and then introduce a new crossover operator to avoid such drawback and to increase efficiency. Also we compare it with several crossover operators for symmetric traveling salesman problem (STSP) for showing the performance of the proposed crossover. Finally, we introduce an efficient simple hybrid genetic algorithm using the proposed operator and then the quality and efficiency of the obtained results are discussed.
Keywords
Genetic Algorithm; Crossover Operator; Symmetric TSP;
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