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A Conservation Genetic Algorithm for Optimization of the E-commerce Logistics Distribution Path

机译:一种保守遗传算法的电子商务物流配送路径优化

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E-commerce is a business activity that uses modern information technology to process cash flow and logistics to achieve transactions. Under the e-commerce environment, an item can reach to the customer accurately is a key factor to enhance the company's image. Therefore, how to efficiently select the algorithm to solve the vehicle routing problem is an urgent problem to be solved. Aiming at the problems existing in the logistics distribution of e-commerce, this paper combines the genetic algorithm with the conservation algorithm based on the maximum travelable distance of the vehicle, and uses the conservation algorithm to generate the initial solution of the genetic algorithm, and constructs the conservation genetic algorithm to solve the e-commerce environment logistics distribution path optimization problem. The simulation results show that the conservation genetic algorithm is more globally optimal than the genetic algorithm.
机译:电子商务是一种使用现代信息技术来处理现金流量和物流以实现交易的商业活动。在电子商务环境下,能够准确地到达客户的物品是提升公司形象的关键因素。因此,如何有效地选择算法来解决车辆路径问题是亟待解决的问题。针对电子商务物流配送中存在的问题,本文基于车辆的最大可行驶距离,将遗传算法与守恒算法相结合,并利用该守恒算法生成了遗传算法的初始解。构建保护遗传算法,解决电子商务环境物流配送路径优化问题。仿真结果表明,保守遗传算法比遗传算法具有更好的全局最优性。

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