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Original Articles Open Access
In order to achieve the goal of energy saving and emission reduction in logistics delivery vehicles, to achieve low cost low exhaust pollution in logistics distribution path optimization, that is to find the reasonable application of algorithm optimize the path. In view of the shortages of existing genetic algorithm and ant colony algorithm which have the characteristics of some limitations, such as ant colony algorithm's convergence slow, easy going, the characteristics of such as genetic algorithm premature convergence in the process of path optimization, process complex, integrating and improving the ant colony algorithm and genetic algorithm in order to solve logistics route optimization problem. At last, through simulation experiment, it is proved that the improved genetic ant colony algorithm is correct and effective.
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Author(s): Shanhong Zhu Weipeng Dong and Wei Liu
Genetic algorithms, Ant Colony Algorithm, Genetic Ant Colony Algorithm, Route Optimization, optimization, algorithm