基于改进粒子群算法的多目标应急物资调度

Multi-objective Emergency Supplies Scheduling Based on Improved Particle Swarm Optimization

围绕突发事件应急的特点,建立了运输成本最小、延误时间最短的多目标数学模型。通过范数理想点将多目标模型转化为单目标模型。设计粒子群优化算法,采用将学习因子、惯性权重设为线性变化和增加局部扰动的方式,建立了针对性的优化算法。结合实际应急案例进行了数值实验与案例分析,证明了算法的有效性,从而为应急条件下的物资调度提供了有效和可靠的方法。

For the problem of emergency supply scheduling , it should minimize both transportation cost and time delay .A multi-objective optimization model is established for this problem .This model is conver-ted to a single objective model by using technique for order preference by similarity to ideal solution . Then, particle swarm optimization algorithm is designed to solve the problem by setting learning factor and inertia weight to linear and increasing local perturbation .With the help of an empirical analysis in combi-nation with the example , the algorithm is proved suitable and valid .This is an effective and reliable ap-proach for emergency supply scheduling .