大规模定制下3D单元布局优化

3D Cellular Layout Optimization Under Mass Customization

针对考虑了可选加工路径、工艺约束、机器实际尺寸和摆放方向以及单元内机器间的距离和单元间的通道距离等诸多实际生产因素的单元构建与3D单元布局集成优化问题,建立了以总搬运成本最小为目标的数学规划模型,并提出了一种改进萤火虫算法(improved fire-fly algorithm,IFA)对该模型进行求解。首先,设计了一种离散化策略来建立IFA与单元构建与3D单元布局集成优化问题的联系;其次,设计了考虑各制造单元间机器数量平衡性的非法解修复策略,以保证算法迭代的有效性;接着,设计了包含3种邻域结构的局部搜索策略来加强算法的局部探索能力;最后,利用不同的算法对测试案例进行仿真求解。结果表明,改进萤火虫算法在求解单元构建与3D单元布局集成优化问题中具有较好的求解效率和优化效果,能够有效地降低总搬运成本。

Aiming at the integrated optimization problem of cellular formation and 3D cellular layout,which considers many practical production factors,such as optional processing paths,process constraints,actual size and placement direction of machines,the distance between machines within a cell,and channel the distance between cells,a mathematical programming model was established to minimize the total transportation cost,and an improved fire-fly algorithm(IFA)was proposed to solve the model.Firstly,a discretization strategy was designed to establish the connection between IFA and cellular formation and 3D cellular layout integration optimization problem.Secondly,an illegal solution repair strategy was designed considering the balance of the number of machines among manufacturing cells to ensure the effectiveness of algorithm iteration.Then,a local search strategy including three neighborhood structures was designed to strengthen the local exploration ability of the algorithm.Finally,different algorithms were used to simulate and solve the test cases.The results show that the improved fire-fly algorithm has batter efficiency and optimization effect in solving the integration optimization problem of cellular formation and 3D cellular layout,and can effectively reduce the total transportation cost.