应急救援下需求分配与网络配流研究

应急救援下,需求的不确定性和交通网络及流量的不稳定性增加了应急决策的难度,救援效果也无法有效控制.考虑模糊需求下应急物资的需求分配与网络配流问题,文章建立了以最小总配送时间为目标的网络流模型.应用基于双边约束的重力模型算法和凸组合算法,通过需求分配和网络流分配结果的交互迭代,得出最小总配送时间下的最优需求分配、路径和网络流.最后,通过算例验证了算法的有效性并对比了不同需求分配机制对救援决策效果的影响,结果表明基于距离阻抗的需求分配机制比基于时间阻抗的分配机制得到的最优解更稳定.

Demand allocation and network flow assignment under emergency rescue circumstance

Under emergency rescue circumstance, the uncertainty of demand and instability of traffic network flow increase the difficulty of emergency decision, and the rescue effect is hard to control. Considering the problem of demand allocation and network flow assignment with fuzzy demand, a network flow model with the objective function of minimum total distribution time was built. By applying the double constrained gravity model and convex combination algorithm, the iterations of demand allocation and network flow assignment result contributed to the best demand allocation, optimal vehicle route and network flow. The effectiveness of the algorithm was verified by experiment tests and the effect of different demand allocation mechanism was compared. Result showed that the distance impedance returns a more stable solution than time impedance.