Abstract: Discrete intelligent factory is one of the research hotspots of intelligent manufacturing,and intelligent manufacturing cell have received extensive attention as an important part.For the layout of intelligent manufacturing cell with a wide variety of processing products and large facilities,a three-dimensional U-shaped intelligent manufacturing cell (3D-UIMC) was proposed.A double objective function with the shortest logistics handling distance and the lowest celluar height was established,and the constraints were defined.Based on the solution of existing algorithms,the Self-Adapting Multi-Objective Fruit Fly Optimization Algorithm (SMFOA) was proposed.The fast non-dominated sorting was used for multi-objective food concentration calculations,the adaptive olfactory search and visual search were designed,and the perturbation operation was used to ensure population diversity.Combined with the example analysis,the results showed that SMFOA had better population diversity,optimization ability and stability performance in solving the facility layout problem of 3D-UIMC.

Key words: intelligent manufacturing cell, three-dimensional U-shaped manufacturing, self-adapting fruit fly optimization algorithm, multi-objective fruit fly optimization algorithm, intelligent factory

摘要： 目前离散型智能工厂已成为智能制造的研究热点之一,智能制造单元作为其重要组成部分也受到广泛关注。针对加工产品种类繁多,设施量大的智能制造单元布置,提出一种立体U型(3D-U)智能制造单元,建立了物流搬运距离最短和单元高度最低的双目标函数,并明确了约束条件。在已有算法研究的基础上,提出了自适应多目标果蝇算法求解3D-U型智能制造单元的设施布置问题,将快速非支配排序用于多目标的食物浓度计算,设计了自适应的嗅觉搜索和视觉搜索,并对飞行策略采用摄动操作来保证种群的多样性。通过算例分析表明自适应多目标果蝇算法在求解3D-U型智能制造单元的设施布置问题时,在种群多样性、寻优能力、稳定性等方面表现优异。

关键词: 智能制造单元, 立体U型制造, 自适应果蝇算法, 多目标果蝇算法, 智能工厂