基于需求紧迫度排序的震后伤员转运问题的协同优化研究

Reasearch on collaborative optimization of post-earthquake casualty transfer problem based on demand urgency ranking

为了合理分配应急救援车辆,缩短救援时间,从受灾区域造成的损坏数据出发,利用Critic权重法对受灾点的紧迫度进行排序,基于排序结果构建异构车辆协同优化模型,通过改进自适应遗传算法求解出最优的车辆分配方案,并以2010年玉树“4·14”地震为例,与不考虑需求紧迫度排序的转运方案和考虑紧迫度排序的单一车型转运方案进行对比。研究结果表明:异构车辆协同运送方案使救援总时间减少13.79%,总成本减少13.82%,满意度提高8.33%,验证该模式的高效性和公平性。研究结果可为政府部门制定有效的应急方案提供可靠参考。

In order to reasonably allocate the emergency rescue vehicles and shorten the rescue time,starting from the damage data caused by the affected area,the urgency of the affected points were sorted using the Critic weighting method.A cooperative optimization model of heterogeneous vehicles was constructed based on the sorting results,and the optimal vehicle allocation scheme was solved through the improvement of adaptive genetic algorithm.Taking the the 2010 Yushu“4·14”earthquake as an example,the scheme was compared with the transfer scheme without considering the demand urgency sorting and the single vehicle type transfer scheme considering the demand urgency sorting.The results show that the cooperative transportation scheme of heterogeneous vehicles reduces the total rescue time by 13.79%,reduces the total cost by 13.82%,and improves the satisfaction by 8.33%,which verifies the efficiency and fairness of the model.The results can provide a reliable reference for government departments to develop effective emergency programs.