物流服务供应链订单分配优化及其遗传算法

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NP-hard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。

Genetic Algorithm to Logistics Service Supply Chain Order Allocation Problem

The transaction costs are proportional to the transaction volume in LSSC order allocation problem. Considering this characteristic, the transaction costs are expressed as linear function. A new mixed integer programming model for LSSC order allocation problem is established, so as to minimize the transaction costs, purchasing costs, rejected units and late delivered units. Because it is NP-hard in nature, a genetic algorithm combined with a heuristics rule is developed to solve the model and to avoid the illegal initial solutions. Random instances show that the model provides systemic simulation for the whole decision-making process and reflects the linear transaction costs factor. And the results of GA are stable and acceptable in allowable CPU time. Computational experiments show that the GA heuristic algorithm outperforms LINGO with respect to solution quality and computational time when the instances become larger.