基于改进飞蛾扑火算法的应急资源调度研究*

为解决多灾害点应急资源调度问题，构建不同路况下运输消耗成本最低、装车时间最少的多目标应急资源调度模型，基于双自适应因子改进飞蛾扑火算法，克服传统飞蛾扑火算法存在的局部最优而早熟收敛、种群多样性低而全局寻优性能差的问题，提高算法的寻优性能和求解精度，并求解应急资源调度问题，获得各灾害点高效应急资源配置方案。研究结果表明:与经典飞蛾扑火优化（MFO）算法以及基于Levy飞行的飞蛾扑火优化（LMFO）算法相比，基于双自适应因子的改进MFO（DAMFO）算法模型求解精度更高，研究结果可为制定合理高效的应急资源调度方案提供依据。

Research on emergency resource scheduling based on improved moth-flame algorithm

In order to solve the problem of emergency resource scheduling for multiple disaster points after the disaster accident,a multi-objective emergency resource scheduling model with the lowest transportation consumption cost and the least loading time under different road conditions was constructed to obtain the emergency resource scheduling scheme of each disaster point.The moth-flame optimization algorithm was improved based on the double adaptive factors,and it overcame the problems of local optimization but premature convergence and low population diversity but poor global optimization performance of the traditional moth-flame algorithm,and enhanced the optimization performance and solving accuracy.The constructed model and algorithm were used to simulate and solve the problem of emergency resource scheduling,and the efficient emergency resource allocation schemes for each disaster point were obtained.The results showed that compared with the common used moth-flame optimization (MFO) algorithm and the moth-flame optimization algorithm based on Levy flight (LMFO),the improved MFO algorithm based on double adaptive factors (DAMFO) had higher accuracy of model solution,which can provide relatively satisfactory emergency resource scheduling scheme.