改进人工人群搜索算法在基于LBS物流配送中的应用  

Seeker Optimization Algorithm with Improved Potential Field for Logistics of LBS

作　　者：张奇松[1] 杨晓光[1] 陈倩[1] ZHANG Qi-song, YANG Xiao-guang, CHEN Qian(Dalian Neusoft Institute of Information, Dalian 116023, Chin)

机构地区：[1]大连东软信息学院,辽宁大连116023

出　　处：《内蒙古大学学报（自然科学版）》2018年第2期212-216,共5页Journal of Inner Mongolia University：Natural Science Edition

基　　金：辽宁省自然科学计划重点项目(20170540051);大连市青年科技之星项目支持计划

摘　　要：以基于LBS物流系统的物流车辆路径规划为研究对象,将一种改进人工势场法与人群搜索算法相结合,对LBS系统中物流车辆的路径规划进行优化.该算法首先利用LBS系统获取环境信息,包括车辆、目标和障碍物的位置和速度信息,其次在基本人工势场法的基础上加入速度因子,使配送车辆初步形成能躲避障碍物并追踪动态物流对象的可行性路径,随后利用人群搜索算法,在可行性路径中搜索最短路径,进而生成物流车辆至动态物流对象的最优路径.该算法有效的将改进式人工势场法和人群搜索算法紧密结合在一起,通过仿真实验证明了该算法在基于LBS的物流系统中物流配送路径规划的有效性,同时将该算法与传统路径规划A*算法进行对比,证明该算法有效的提高了系统中的整体搜索效率.Logistics vehicle routing planning of logistics system based on LBS is studied. An im- proved artificial potential field method and seeker optimization algorithm are combined to optimize logistics vehicle path planning in LBS system. Firstly,the algorithm uses the LBS system to obtain environmental information, including the location and speed information of the vehicle, the target and the obstacle. Secondly, the algorithm adds speed factor to the basic artificial potential field method,making feasibility path that can avoid obstacles and tracking dynamic logistics object, then uses seeker optimization algorithm to search the shortest path in the feasibility of the path, and gen- erates the optimal path for logistics vehicles. The algorithm combines the improved artificial poten- tial field method and seeker optimization algorithm efficiently. The simulation experiments show that the algorithm is effective in logistics distribution based on LBS,and are compared with the tra- ditional A^＊ algorithm,this algorithm improves the overall search efficiency.

关 键 词：LBS 改进式人工势场 人群算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]