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本文以现金物流为研究背景,不同于以往对客户需求的研究,提出了一类考虑客户券别要求的现金押运路线问题,并以现金券别均衡和运输成本减少为目标,建立了相应的混合整数规划模型。根据模型的性质,设计了一种基于局部搜索和多样性管理机制的遗传算法进行求解。数值实验对模型特性和算法性能进行了分析,结果表明券别因素增加了运输成本,影响了押运路线,改进的遗传算法能求解更大规模的问题,得到质量较好的解。
This dissertation takes cash logistics as the research background. Different from the previous research on customer demand, this paper proposes a kind of cash escort route considering the requirements of customer coupons. With the goal of balance of cash voucher and reduction of transportation cost, a corresponding hybrid Integer programming model. According to the nature of the model, a genetic algorithm based on local search and diversity management mechanism is designed to solve the problem. Numerical experiments are carried out to analyze the characteristics of the model and the performance of the algorithm. The results show that the cost of transportation increases the transportation cost and affects the escort route. The improved genetic algorithm can solve the problem of larger scale and get a better solution.