TY - GEN
T1 - A high performance hybrid metaheuristic for traveling salesman problem
AU - Tsai, Chun Wei
AU - Chen, Jui Le
AU - Tseng, Shih Pang
AU - Chiang, Ming Chao
AU - Yang, Chu Sing
PY - 2010/12/1
Y1 - 2010/12/1
N2 - Genetic algorithm (GA) is one of the most widely used metaheuristics in finding the approximate solutions of complex problems in a variety of domains. As such, many researchers have focused their attention on enhancing the performance of GA - in terms of either the speed or the quality but rarely in terms of both. This paper presents an efficient hybrid metaheuristic to resolve these two seemingly conflicting goals. That is, the proposed method can not just reduce the running time of GA and its variants, but it can also make the loss of quality small, called High Performance Hybrid Metaheuristic (or HPHM for short). The underlying idea of the proposed algorithm is to leverage the strengths of GA, Tabu Search, and the notion of Pattern Reduction. To evaluate the performance of the proposed algorithm, we use it to solve the traveling salesman problem. Our experimental results indicate that the proposed algorithm can significantly enhance the performance of GA and its variants - especially the speed.
AB - Genetic algorithm (GA) is one of the most widely used metaheuristics in finding the approximate solutions of complex problems in a variety of domains. As such, many researchers have focused their attention on enhancing the performance of GA - in terms of either the speed or the quality but rarely in terms of both. This paper presents an efficient hybrid metaheuristic to resolve these two seemingly conflicting goals. That is, the proposed method can not just reduce the running time of GA and its variants, but it can also make the loss of quality small, called High Performance Hybrid Metaheuristic (or HPHM for short). The underlying idea of the proposed algorithm is to leverage the strengths of GA, Tabu Search, and the notion of Pattern Reduction. To evaluate the performance of the proposed algorithm, we use it to solve the traveling salesman problem. Our experimental results indicate that the proposed algorithm can significantly enhance the performance of GA and its variants - especially the speed.
UR - http://www.scopus.com/inward/record.url?scp=78651447219&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:78651447219
SN - 9781424496730
T3 - 2010 World Automation Congress, WAC 2010
SP - 1
EP - 6
BT - 2010 World Automation Congress, WAC 2010
T2 - 2010 World Automation Congress, WAC 2010
Y2 - 19 September 2010 through 23 September 2010
ER -