CAJ | 학술논문

车辆优化调度是提高物流企业运营效益的重要因素，针对标准粒子群优化算法存在的不足，提出一种改进粒子群算法（IPSO）的物流配送车辆调度优化方法。建立物流配送车辆调度优化的数学模型，将车辆与车辆路径编码成粒子，通过粒子之间的协作找到最优物流配送车辆调度优化方案，并对粒子群算法存在的不足进行了相应的改进，最后给出仿真实验对其性能进行测试。实验结果表明，IPSO算法不仅加快了物流配送车辆调度优化问题求解的速度，而且获得了最优解的概率，具有比其他调度算法更明显的优势。
차량우화조도시제고물류기업운영효익적중요인소，침대표준입자군우화산법존재적불족，제출일충개진입자군산법（IPSO）적물류배송차량조도우화방법。건립물류배송차량조도우화적수학모형，장차량여차량로경편마성입자，통과입자지간적협작조도최우물류배송차량조도우화방안，병대입자군산법존재적불족진행료상응적개진，최후급출방진실험대기성능진행측시。실험결과표명，IPSO산법불부가쾌료물류배송차량조도우화문제구해적속도，이차획득료최우해적개솔，구유비기타조도산법경명현적우세。
Vehicle routing scheduling is an important factor to improve the operation efficiency of logistics enterprises, to solve the defects of the standard particle swarm optimization algorithm, an improved particle swarm optimization algorithm for vehicle routing problem of logistics distribution is proposed. Firstly, the mathematical model for vehicle routing problem of logistics distribution is established, and then the vehicle and vehicle routing are encoded into particles, the optimal scheme for vehicle routing problem of logistics distribution is found by the collaboration between particles in which de-fects of the particle swarm algorithm are improved, finally the simulation experiment is used to test the performance. The results show that the proposed algorithm not only accelerates the solving speed, but also increases the obtaining the optimal solution probability or vehicle routing problem of logistics distribution problem, and has some advantages than other scheduling algorithms.