考虑服务时效的物流服务供应链应急任务分配

Coordinating emergency task allocation of logistics service supply chain under time-to-service

针对应急情况下两级物流服务供应链任务分配问题,提出了考虑服务时效性的客户满意度模型方法。首先,考虑应急情况中订单任务量的随机性的情况,建立基于服务时效性的客户满意度模型;其次,构建最小化物流成本模型以保证物流服务供应链成本最优化;然后,引入线性加权法将包含最大化客户满意度与最小化服务成本双层规划多目标模型转化为单目标模型;最后,采用遗传算法(GA)求解模型,并针对权重作了灵敏度分析。算例研究表明,与上下层单目标分配结果的目标值0.050 1和0.082 5相比,综合函数模型得到了显著优化的目标值0.271 6,说明所构建模型的任务分配方案能够更有效解决具有服务时效性客户满意度的物流服务供应链任务分配问题;由分析权重灵敏度可以看出,权重0.1<a<0.5时的综合目标优化解相较于0.5<a<0.9斜率变化程度显著,说明在应急任务分配时应根据服务能力参数理性选择两者的权重分配,这反映出了客户满意与物流成本悖反效应的存在。研究结果表明,考虑服务时效的任务分配模型能够有效解决应急情况下物流服务供应链任务分配问题。

Aiming at the task allocation problem of two echelon logistics service supply chain in emergency, a customer satisfaction model with time-to-service was put forward. First of all, considering the randomness of orders in emergency, the customer satisfaction model with time-to-service was established. Secondly, the minimum logistics cost model was established to ensure the optimization of logistics service supply chain cost. Again, using linear weighted method, multi-objective model including maximizing customer satisfaction and minimizing service cost was transformed into single-objective model. At last, Genetic Algorithm （GA） was used to solve this model, and sensitivity analysis was used to analyze the weight. Results of calculation example show that compared with target value of 0. 050 1 and O. 082 5 of single-objective assignment, the comprehensive function model can obtain the optimal target value of 0. 271 6, which means the task allocation scheme of the established model can effectively solve task allocation problem of customer satisfaction with time-to-service. Analysis of weight sensitivity shows that when the weight is between 0. 1 and 0.5, the optimal solution is more significant in slope variation degree compared to the weight of 0. 5 to 0.9, which indicates that it should be more rational to choose allocation weight according to service ability parameter when allocating tasks in emergency, and paradox effect of customer satisfaction and logistics cost exists in the emergency task allocation. The results indicate that the task allocation model with time-to-service can effectively solve task allocation problem of logistics service supply chain in emergency.