基于混合蚁群粒子群算法的立体库堆垛机路径优化

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英文篇名：Path Optimization of Stereoscopic Warehouse Stacker Based on Mixed Ant Colony Particle Swarm Algorithm 作者：陈晨 ; 茅健 英文作者：CHEN Chen;MAO Jian;School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science; 关键词：智能物流 ; 堆垛机 ; 蚁群算法 ; 粒子群算法 ; 路径优化 英文关键词：intelligent logistics;;stacker;;ant colony algorithms;;particle swarm algorithm;;path optimization 中文刊名：QGJX 英文刊名：Light Industry Machinery 机构：上海工程技术大学机械与汽车工程学院; 出版日期：2019-08-06 出版单位：轻工机械 年：2019 期：v.37;No.160 基金：上海工程技术大学研究生科研创新项目(E3-0903-18-01008) 语种：中文; 页：QGJX201904013 页数：5 CN：04 ISSN：33-1180/TH 分类号：68-71+77

摘要

针对自动化立体仓库中的堆垛机路径优化问题,课题组通过分析立体仓库中堆垛机的工作特点与运行情况,提出了基于混合蚁群粒子群算法的路径优化方法,在传统的蚁群算法中结合粒子群算法思想,使算法同时具备蚁群算法的正反馈与粒子群的多样性。通过对实例进行MATLAB仿真分析表明:混合算法路径优化速度较快,且比以往的路径更短。研究使堆垛机的运行效率得到提高。
        In order to solve the problem of crane path optimization in automated warehouse,research project's group first analyzed the working characteristics of the crane in warehouse and the situation of the path,a path optimization method based on hybrid ant colony particle swarm optimization was proposed. In the traditional ant colony algorithm,particle swarm algorithm thought was combined to make the algorithm have a combination of positive feedback of ant colony algorithm and particle swarm diversity. Through the simulation,the algorithm path optimization speed becomes faster,and the path is shorter than ever before. This research improves the operation efficiency of stacker.

引文

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