A fast parallel genetic algorithm for traveling salesman problem

Authors:
Chun-Wei Tsai;Shih-Pang Tseng;Ming-Chao Chiang;Chu-Sing Yang
Affiliations:
Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan and Electrical Engineering, National Cheng Kung University, Tainan, Taiwan;Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan and Computer Science and Information Engineering, Tajen University, Pingtung, Taiwan;Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan;Electrical Engineering, National Cheng Kung University, Tainan, Taiwan
Venue:
MTPP'10 Proceedings of the Second Russia-Taiwan conference on Methods and tools of parallel programming multicomputers
Year:
2010

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Abstract

In this paper, we present a fast scalable method to reduce the computation time of genetic algorithms for traveling salesman problem, called the Parallel Pattern Reduction Enhanced Genetic Algorithm (PPREGA). The general idea behind the proposed algorithm is twofold: (1) Eliminate the redundant computations of GA on its convergence process by pattern reduction and (2) Minimize the completion time of GA by parallel computing. Our simulation result shows that the proposed algorithm can significantly reduce not only the computation time but also the maximum completion time of GA. Moreover, our simulation result shows further that the loss of the quality of the end result is small.