现代电子技术2024，Vol.47Issue(24)：177-186,10.DOI:10.16652/j.issn.1004-373x.2024.24.028
基于改进秃鹰搜索算法的汽车零部件生产车间调度优化
Automobile parts production workshop scheduling optimization based on improved bald eagle search algorithm
摘要
Abstract
Automobile is an indispensable transportation in modern society.In order to realize the efficient production of its components,an intelligent production scheduling model with the goal of minimizing the maximum completion time is established,and a mixed optimization bald eagle search(MOBES)algorithm with mixed optimization strategies is proposed.The algorithm is discretized by means of ROV coding method and forward and backward decoding of FAMFR and FCFS.The heuristic rules and backward learning strategies are introduced in population initialization,optimal insertion and optimal exchange strategies,neighborhood search strategies and multi-point crossover strategies are added in the process of algorithm iteration,and local search strategies are performed on the optimal solution,so that the algorithm can better cope with the problems such as local optimality global search,and local development mismatches.The data are tested by Carlier testing set and a real case of an automobile parts manufacturing plant,and compared with other algorithms.The experimental results verify the effectiveness of the bald eagle search algorithm on the production workshop scheduling problem and the superiority of its algorithmic hybrid optimization strategy.关键词
车间调度/秃鹰搜索算法/汽车零部件/启发式规则/反向学习策略/邻域搜索策略/局部搜索策略Key words
workshop scheduling/bald eagle search algorithm/automobile parts/heuristic rules/reverse learning strategy/neighborhood search strategy/local search strategy分类
信息技术与安全科学引用本文复制引用
石庆升,石成钰..基于改进秃鹰搜索算法的汽车零部件生产车间调度优化[J].现代电子技术,2024,47(24):177-186,10.基金项目
国家自然科学基金资助项目(62333013) （62333013）
河南省高等学校青年骨干教师培养计划项目(2019GGJS095) （2019GGJS095）
