Abstract
In order to solve traveling salesman problems that employed completion- time- shortest as the evaluating rule, an encoding method and improved differential evolution algorithm were proposed. In these methods, real number encoding and roulette wheel selection were adopted for improved differential evolution and neighborhood search operator was devised. It was fit for solving symmetric and asymmetric multiple traveling salesman problem. Asymmetric multiple traveling salesman problems were simulated. By comparison with the results of genetic algorithm and standard differential evolution, it is shown that the improved differential evolution algorithm proposed in this paper is efficient to solve the discrete combinatorial problem, such as optimization of multiple traveling salesman problems.
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Zhou, H., Wei, Y. (2010). Optimization of Minimum Completion Time MTSP Based on the Improved DE. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13495-1_60
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DOI: https://doi.org/10.1007/978-3-642-13495-1_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13494-4
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