物流服务供应链订单分配优化及其遗传算法

发布时间：2018-06-18 05:50

本文选题：供应链 + 混合整数规划模型　；参考：《运筹与管理》2014年05期

【摘要】：针对物流服务供应链订单分配问题中,物流服务集成商通常会按照所分配的订单价值向分包商收取一定比例交易费用的特点,设定交易费用为交易额的线性函数,构建了新的物流服务供应链订单分配优化混合整数规划模型,其优化目标为最小化交易费用、采购费用、短缺服务与延迟供给的物流能力数量。鉴于问题的NPhard特性,设计了相应的遗传算法,并结合基于优先权的启发式规则避免了大量非法初始解的出现。实验算例表明所建立的模型能够反映物流服务供应链订单分配过程中的线性交易费用因素,其所设计的算法能够在可接受的时间内获得质量较高的满意解,并且对于大规模订单分配优化问题,遗传算法的求解时间与求解结果要优于LINGO软件。
[Abstract]:In the logistics service supply chain order allocation problem, the logistics service integrator usually collects a certain proportion of the transaction cost from the sub-contractor according to the value of the order assigned, and sets the transaction cost as a linear function of the transaction value. A new mixed integer programming model for order allocation optimization in logistics service supply chain is constructed. The optimization goal is to minimize transaction cost, purchase cost, logistics capacity of short service and delayed supply. In view of the NPhard property of the problem, the corresponding genetic algorithm is designed, and a large number of illegal initial solutions are avoided by combining the heuristic rules based on priority. An experimental example shows that the proposed model can reflect the linear transaction cost factors in the order allocation process of the logistics service supply chain, and the algorithm designed by the model can obtain a satisfactory solution of high quality in acceptable time. For large-scale order allocation optimization problem, the solving time and result of genetic algorithm are better than lingo software.
【作者单位】：河南理工大学经济管理学院;
【基金】：国家自然科学基金资助项目(71272219) 教育部人文社科基金规划项目(11YJA630067) 河南省软科学研究项目(112400450285)
【分类号】：F274;F252

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