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Study on hybrid heuristic algorithm for multi-depot vehicle routing problem with hybrid picking-delivery strategy

机译:混合拣货输送策略多仓车辆路由问题混合启发式算法研究

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With the rapid development of electronic commerce and logistics distribution, multi-depot vehicle routing problem with backhauls (MDVRPB) as influencing electronic commerce more step development, has been paid more attentions. According to the characteristics of model, hybrid heuristic algorithm is used to get the optimization solution. First of all, use hybrid coding so as to simplify the problem; construct the pertinence of initial solution to enhance the feasibility of solutions. Improved partially matched crossover operators can avoid destroying good gene parts during the course of crossover. According to the traditional genetic algorithm shortcomings of slowly convergent speed, the study adopts the strategy of protecting gene as whole, introduce adopts 2- exchange mutation operator. Secondly, stock elite adopting genetic algorithm with taboo searching algorithm to improve the convergent speed. This algorithm can offer the thought to settle the practical problem in scale. At the same time, it can be known that adopting hybrid picking-delivery strategy can save the distance of distribution route so as to improve economic benefit.
机译:随着电子商务和物流分布的快速发展,逆向(MDVRPB)的多仓车辆路由问题作为影响电子商务更多步骤开发,已得到更多的注意。根据模型的特征,混合启发式算法用于获得优化解决方案。首先,使用混合编码以简化问题;构建初始解决方案的解决方案,以提高解决方案的可行性。改进的部分匹配的交叉运算符可以避免在交叉过程中销毁良好的基因零件。根据传统的遗传算法慢慢收敛速度的缺点,研究采用整体保护基因的策略,引入采用2-交换突变算子。其次,具有采用禁忌搜索算法的遗传算法的库存精英提高收敛速度。这种算法可以提供思考,以规模地解决实际问题。同时,可以知道采用混合拣选输送策略可以节省分销路线的距离,以提高经济效益。

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