一种基于多种群NSGA-Ⅱ的卷烟厂多AGV调度方法
NSGA-Ⅱ Based on Multi-Population for Multi-AGV Scheduling in Cigarette Factory
李勇健 1吴珂雨1
作者信息
- 1. 江苏中烟工业有限责任公司南京卷烟厂,江苏 南京 210019
- 折叠
摘要
在卷烟厂生产实践中,自动导引车是助力生产自动化和智能化的重要运输工具.针对AGV应用过程中出现的AGV数量和系统作业效率的冲突,以用车数量最小化和系统作业时间最小化为优化目标,构建卷烟厂多AGV调度优化模型.为求解该问题,设计一种多种群的NSGA-Ⅱ算法,引入多种交叉算子强化算法的全局探索能力,构建三个群从不同方向对Pareto最优解进行探索,设计启发性邻域搜索策略提高算法收敛性.基于实际工作环境,构建了四个规模不同的测试算例,并通过与其他经典的多目标优化算法对比,验证所提算法能够获取收敛性和分布性较好的Pareto解集,为AGV调度提供决策方案.
Abstract
Aiming at the contradictory between the number of AGVs and the operating efficiency during the process of AGV application,the multi-AGV scheduling optimization model for the ingredient transportation system of a cigarette factory is established,to minimize the vehicle number and the makesapn.To solve this problem,a multi-population NSGA-Ⅱ algorithm is designed,where a variety of crossover operators are introduced to strengthen the global exploration ability of the algorithm,three subpopulations are constructed to explore Pareto optimal solutions from different directions,and the heuristic neighbor-hood search strategy is designed.According to the practical working environment,four test instances with different scales are constructed.By comparing with other classical multi-objective optimization algorithms,it is verified that the proposed algorithm can obtain the Pareto solution set with good convergence and distribution,providing decision schemes for AGV scheduling.
关键词
卷烟厂/多种群/NSGA-Ⅱ/多AGV调度/变邻域搜索Key words
cigarette factory/multi-population/NSGA-Ⅱ/multi-AGV scheduling/variable neighborhood search引用本文复制引用
出版年
2024
NETL
NSTL
万方数据