摘要
为提高物料运输调度效率,减少作业时间,将2批次物料投递问题划分为3个阶段,将3个阶段的总作业时间最少作为目标函数,提出了一个混合整数规划模型。通过定义单双向车道约束和运输车辆路口会车约束,并引入多种群遗传算法,研究了多台物料运输小车的物料投递作业调度模型及算法。与单种群遗传算法和某公司历史数据相比,结果表明:该算法可在避免局部搜索的基础上大幅度提高系统的运算精度与速度,减少物料配送时间,可靠性高。该研究结果为提高企业的经济效益提供了参考,也为多批次物料投递作业优化及决策提供了新的思路。
In order to improve the efficiency of material transportation scheduling and reduce the operation time,the problem of 2 batches of material delivery was divided into 3 stages.The minimum total operation time of the 3 phases was used as an objective function,a mixed integer programming model was proposed.Single and two-way lane constraints and the constraints of vehicles meeting at intersections were defined,and the multiple population genetic algorithm was introduced to study the material delivery scheduling model and algorithm of multiple material transportation vehicles.Compared with the single population genetic algorithm and the historical data of a company,the results show that by using the algorithm,the accuracy and speed of the system are greatly improved on the basis of avoiding local search,the material delivery time is reduced,and the reliability is improved.The research results provide a reference for improving the economic benefits of enterprises,and also provide new ideas for the optimization and decision-making of multi-batch material delivery operations.
作者
曹春玲
李咪
高文星
李梦雨
CAO Chunling;LI Mi;GAO Wenxing;LI Mengyu(College of Mechanical Engineering,Xi’an University of Science and Technology,Xi’an Shaanxi 710054,China)
出处
《机床与液压》
北大核心
2020年第17期146-151,共6页
Machine Tool & Hydraulics
关键词
物料运输调度
多种群遗传算法
路径规划
多批次
Material transportation scheduling
Multi-population genetic algorithm
Path planning
Multi-batch
