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- W3176550350 abstract "Abstract An improved genetic algorithm is proposed to solve the traveling salesman problem. On the basis of traditional genetic algorithm, greedy algorithm is introduced to initialize the population. The genetic parameters are adjusted adaptively from two aspects of genetic evolution algebra and individual fitness function value, which can speed up the optimization speed and prevent the optimization from falling into local optimum. In mutation operation, adaptive algorithm is used to select mutation operator to improve the quality of variation and search effect of the algorithm; after individual evolution, one-way evolutionary reversal operation is introduced to improve the chance of inheriting parent and parent genes, and improve the ability of algorithm to search for optimal solution." @default.
- W3176550350 created "2021-07-05" @default.
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- W3176550350 date "2021-06-01" @default.
- W3176550350 modified "2023-10-16" @default.
- W3176550350 title "An Improved genetic algorithm for solving TSP" @default.
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- W3176550350 doi "https://doi.org/10.1088/1742-6596/1952/4/042067" @default.
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