摘要
针对可重构制造系统的快速配置提出了一种多目标优化方法,考虑3个优化目标:设备负载均衡度、产品生产时间以及产品生产成本。在第三代多目标遗传算法(NSGA-Ⅲ)的基础上结合邻域搜索构建了多目标遗传-邻域搜索算法(NSGA-NS),以从配置解空间中寻找一系列前沿解。通过一个液压阀阀块的制造系统配置案例对算法进行验证,并与归档式多目标模拟退火算法、多目标粒子群算法以及一种改进的多目标粒子群算法进行了比较,结果表明,NSGA-NS与NSGA-Ⅲ在前沿解质量上显著优于其他算法,NSGA-NS在保持了NSGA-Ⅲ的全局寻优性能的同时显著提高了收敛速度和计算速度。
A multi-objective optimization method is proposed for the rapid configuration of reconfigurable manufacturing systems,considering three optimization objectives:equipment load balance,product production time,and product production cost.A multi-objective genetic-neighborhood search algorithm(NSGA-NS)is constructed based on the third generation multi-objective genetic algorithm-Ⅲ(NSGA-Ⅲ)combined with neighborhood search to find a series of front solutions from the configuration solution space.The algorithm is validated by a configuration case of a hydraulic valve block manufacturing system,and compared with the archived multi-objective simulated annealing,multi-objective particle swarm optimization,and an improved multi-objective particle swarm optimization.The results show that NSGA-NS and NSGA-Ⅲsignificantly outperform each other in terms of front solutions quality,NSGA-NS significantly improves the convergence speed and calculational speed while maintaining the global search performance of NSGA-Ⅲ.
作者
洪胡平
张为民
谢树联
HONG Huping;ZHANG Weimin;XIE Shulian(School of Mechanical Engineering,Tongji University,Shanghai 201800,China)
出处
《组合机床与自动化加工技术》
北大核心
2024年第3期1-5,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家重点研发计划资助项目(2022YFE0114100)。
关键词
可重构制造系统
配置
多目标优化
混合启发式算法
reconfigurable manufacturing systems
configuration
multi-objective optimization
hybrid heuristics
