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Directed Graph Optimization Model and its Solving Method Based on Genetic Algorithm in Fourth Party Logistics

机译:基于遗传算法在第四党物流遗传算法的定向图优化模型及其解决方法

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Based on the introduction of the concept of the 4th party logistics and the decision supporting system in its operation, the directed graph model with multi dimension weight was established for its optimization problem of how to select the route, the transportation method and the third party logistics provider concurrently. Genetic Algorithm is used to solve this directed graph model. An adaptive length-variant coding method is employed to represent the individual. The initial group is generated at random. After crossover and mutation are done, individuals are selected according to the rank they obtain when comparison is taken in the sense of fitness, of course randomly and elitism is applied. The results of experiments show that this Genetic algorithm can help to get the optimal solution to the directed graph model and solve the optimization problem in the operation of 4th party logistics.
机译:基于第四方物流概念的概念和决策支持系统的运作,为其如何选择路线,运输方法和第三方物流的优化问题而建立了具有多维重量的定向图模型提供者同时。遗传算法用于解决此定向图模型。采用自适应长度变型编码方法来表示个体。初始组随机生成。在完成交叉和突变之后,根据在适应感上采取的等级选择单个等级,当然,当然是随机和精才主义。实验结果表明,这种遗传算法可以帮助将最佳解决方案获得定向图模型,解决第四届党物流运行中的优化问题。

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