考虑路径风险的需求不确定应急物流定位-路径问题

针对自然灾害对路网造成的破坏性和受灾点物资需求量的不确定性,综合考虑应急物流路径风险和物资分配的时间公平性,将路径风险定量化为路径通行能力风险、路径损毁风险和路径复杂性,基于鲁棒优化理论,以最小化车辆最长配送时间和应急物流系统总成本为目标,建立了双目标多物资定位-路径优化模型,采用遗传算法对其求解,以汶川地震应急救援相关数据为例进行了数据仿真实验。实验结果的对比分析表明:在考虑路径风险下,随着控制系数的增加,系统总成本和最长配送时间目标值均呈现增大的趋势;受灾点的物资需求扰动越大,构建应急物流系统的总成本越高。算例结果也验证了鲁棒优化方法在处理不确定需求方面的有效性,为解决自然灾害后应急设施点的开设和救援物资的安全及时准确配送提供了有效的方法。

Emergency Location-routing Model with Uncertain Demands under Path Risks

Location-routing problem (LRP) is an important logistics problem in emergency management. Considering the risk of road congestion, the risk of road damage, the risk of the road complexity and the demand uncertainty of relief commodities, a multi-objective optimization model based on robust optimization theory aiming at minimizing the longest distribution routine time and the total logistic system cost is developed. Comparison of several cases is made to indicate that the total system cost, the longest path transportation delivery time and the total system cost all show the tendency of increase with the growth of the controlling parameters. The total cost is higher when the demand disruption is greater, which proves the effectiveness of the robust optimization model. It provides an effective method to solve the emergency material security, timely delivery and the risk in emergency logistics system.