摘要
针对汽车零部件车辆配送路径规划问题,提出一种基于IPSO的多目标车辆路径规划算法。以平均行驶成本、等待时间成本和惩罚时间成本为目标函数,建立多目标车辆路径规划模型。研究结果表明,选择搜索成功率、平均行驶成本和搜索时间为评价指标,IPSO算法在搜索成功率和搜索时间以及平均行驶成本方面,均优于GA和PSO算法,同时避免局部最优,对降低配送成本和提升企业竞争力具有重要意义。
In this paper,a multi-objective vehicle route program based on IPSO was proposed to solve the vehicle route problem.The multi-objective vehicle route model was established based on the objective cost,waiting time cost and penalty cost to select the search success rate,average travel cost and search time as the evaluation index.The results showed that the IPSO algorithm in the search success rate and search time and average travel cost was better than GA and PSO algorithm.It is important for avoiding the local optimum,reducing the delivery cost and enhancing the competitiveness of enterprises.
作者
陈智勇
CHEN Zhi-yong(Qinghai Normal University, Xining 810000, China)
出处
《山东农业大学学报（自然科学版）》
CSCD
2017年第2期255-258,共4页
Journal of Shandong Agricultural University：Natural Science Edition
关键词
粒子群算法
路径规划
多目标函数
数学模型
Particle swarm optimization
route program
multi-objective function
mathematical model
