基于改进蜂群算法的模糊需求冷链物流车辆路径优化
Optimization of Cold-chain Logistics Vehicle Routing with Fuzzy Demand by an Improved Artificial Bee Colony Algorithm
姜婷1
作者信息
- 1. 安徽经济管理学院信息工程系,安徽合肥 230059
- 折叠
摘要
针对基本人工蜂群算法容易早熟收敛等问题,提出了3种邻域生成策略,并对当前解进行局部搜索和进化.仿真试验表明,该算法在求解相关问题上具有有效性,对求解用户模糊需求下的冷鲜品冷链物流车辆路径优化问题具有一定的参考价值.
Abstract
Aiming at the premature convergence problem of the basic artificial bee colony algorithm,3 neighborhood generation strategies were proposed,and the local search and evolution of the solution were carried out.Simulation test results showed that the proposed algorithm was effective in solving related problems,and had a certain reference value for solving the cold-chain logistics vehicle routing''s optimization problem of cold and fresh goods under the fuzzy demand of users.
关键词
改进蜂群算法/模糊需求/邻域生成策略/冷链物流车辆路径优化Key words
Improved bee colony algorithm/Fuzzy demand/Neighborhood generating strategy/Cold-chain logistics vehicle routing's optimization引用本文复制引用
基金项目
安徽省哲学社科规划项目(AHSKY2015D71)
安徽省社科创新发展研究课题(A2015020)
安徽省高校优秀青年人才基金重点项目(2013SQRL111ZD)
出版年
2017
国家科技期刊平台
NSTL
维普
万方数据