基于改进粒子群算法的矿山运输调度系统优化

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英文篇名：Optimization of Mine Transportation Dispatching System Based On Improved Particle Swarm Optimization 作者：张科强 英文作者：ZHANG Ke-qiang;Department of Resource Engineering,Ordos Vocational College; 关键词：运输调度模型 ; 粒子群算法 ; 随机变异算子 英文关键词：transportation scheduling model;;particle swarm optimization;;random mutation operator 中文刊名：NMSB 英文刊名：Journal of Inner Mongolia Normal University(Natural Science Edition) 机构：鄂尔多斯职业学院资源工程系; 出版日期：2017-03-15 出版单位：内蒙古师范大学学报(自然科学汉文版) 年：2017 期：v.46;No.184 基金：内蒙古自治区高等学校科学研究项目(NJSC14377);; 内蒙古科技计划资助应用技术研发项目(20120304) 语种：中文; 页：NMSB201702023 页数：6 CN：02 ISSN：15-1049/N 分类号：100-105

摘要

针对露天矿山运输调度系统的优化算法存在流程复杂、收敛速度慢、求解精度低等问题,通过引入随机变异算子对粒子群算法进行改进.用改进的算法对露天矿山运输调度模型优化求解,计算结果表明,相对于常见的几类经典的改进粒子群算法,改进算法具有收敛速度快、精度高的优点,并且解决了标准粒子群算法易早熟和易陷入局部最优的缺点.
        In view of the optimization algorithm for transportation dispatching system in open-pit mine which has problems of the complex process and slow convergence speed and to solve the problem of lower accuracy,The particle swarm optimization was improved by introducing a random mutation operator.With the improved algorithm to optimize the open-pit mine transportation scheduling model,the calculation results show that the improved algorithm has the advantage of fast convergence speed,high precision compared with the common improvement of several classic particle swarm optimization algorithm.It solved the standard particle swarm algorithm prone to premature and the shortcoming of local optimum.

引文

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