基于混合遗传算法的液压元件装配流水车间调度

Hydraulic components assembly flowshop scheduling based on hybrid genetic algorithm

文章以BY公司为背景,研究液压元件装配流水车间调度问题(hydraulic components assembly flowshop scheduling problem,HCAFSP)。通过分析两阶段装配流水车间调度(the two-stage assembly flowshop scheduling problem,TSAFSP)、液压元件生产工艺与车间设施,提出一种新的机器配置和在制品库存计算方法。考虑到该问题的NP难性与BY公司数字化车间升级带来的产能提升,设计一种遗传算法孤岛模型(genetic algorithm island model,IsLandGA)与粒子群优化(particle swarm optimization,PSO)的混合算法(IsLandGA-PSO)。该算法采用圆锥拓扑,圆锥底为IsLandGA,提供全局快速搜索能力;顶点为每个子群的最优个体组成的PSO,提供精准局部搜索能力;利用优势互补和迁移优秀个体完成协同进化。通过多组实例仿真与算法对比,表明该算法求解较大规模HCAFSP问题的有效性和先进性。

This paper takes BY Company as the background to study the hydraulic components assembly flowshop scheduling problem(HCAFSP).By analyzing the two-stage assembly flowshop scheduling problem(TSAFSP),production process of hydraulic components and workshop facilities,this paper proposes a new machine configuration and work in process inventory calculation method.Considering the NP-hardness of the problem and the capacity increase brought by the upgrading of digital workshop in BY Company,a hybrid algorithm(IsLandGA-PSO)of genetic algorithm island model(IsLandGA)and particle swarm optimization(PSO)is designed.The algorithm uses a cone topology,the bottom of the cone is IsLandGA,providing global fast search capabilities;the vertex is the PSO composed of the best individuals in each subgroup,providing precise local search capabilities;complementary advantages and outstanding individual migration are used to complete co-evolution.Through multiple sets of example simulation and algorithm comparison,the effectiveness and advancement of the algorithm in solving large-scale HCAFSP problems are proved.