A comparison of operators for solving time dependent traveling salesman problems using genetic algorithms
作者： Gerry V. Dozier , Leonard J. Testa , Abdollah Homaifar , Albert C. Esterline
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摘要: This paper describes which genetic operators can best solve time dependent traveling salesman problems (TDTSPs) containing up to 50 cities. We first provide an overview of the TDTSP and illustrate its relation other scheduling routing problems. Next we describe a algorithm that implements eight common operators, plus Julstrom's adaptive operator probability Goldberg's population re-initialization mechanisms. present results 280 experiments show one combination these mechanisms outperforms well-known dynamic programming heuristic. An analysis test indicates hybrid solutions incorporating solution techniques for both may generate better than either technique alone.
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