基于PSO城市应急物流最优调度决策的研究

Optimal dispatch decision of city emergency logistics based on particle swarm optimization

在城市应急网络的大背景下,采用粒子群优化算法(PSO),对应急物流的调度进行了研究。自然选择的粒子群优化算法是在基本粒子群算法的基础上改进的算法,相比基本粒子群算法,它用当前较好的粒子代替较差的粒子,通过函数测试,表明自然选择的粒子群算法的精确度和效率都很高。利用自然选择的粒子群算法,在满足应急运输要求的前提下,充分利用各种物流设施,快速组织多种交通工具,制定应急物流最优的调度决策,以保证经济效益的最大化和实现过程的最优化。

Against the background of the city emergency network,the article does some research on the emergency logistics scheduling with particle swarm optimization.Natural selection particle swarm optimization is an algorithm improved from the basic particle swarm algorithm.Different from the old algorithm,it cuts off half of the particles which are bad in velocity and position instead of better ones.The paper also gives the fullest expression to the advantage of NSPSO by a function test.In satisfying the precondition of emergency transport,the algorithm can help make full use of various logistics facilities,fast organize various traffic tools,and make the optimal decision of vehicle routing problem of city emergency logistics,to improve the efficiency of emergency rescue.