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A New Dynamic Cell Formation Model Considering Machine Sequence and Labor- intensive Situation

机译:考虑机器顺序和劳动密集型情况的新型动态细胞形成模型

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This paper presents a new two-phase dynamic cellular manufacturing model in a labor-intensive situation. In the first phase the formation of machines in cells is selected. The output of this phase has been used as an input for the second phase to select the best number of operators. In the first phase objectives are minimizing total cost of material handling, relocation, constant and varying machine utilization, and minimizing machine workload unbalanced simultaneously. In the second phase the objective is minimizing the number of workers. The first phase is solved using hybrid particle swarm optimization (PSO) and epsilon constraint. The second phase is optimized using simulation with Visual Slam. Results are compared with GAMS solver and commercial CPLEX solver.
机译:本文提出了一种劳动密集型情况下的新型两阶段动态蜂窝制造模型。在第一阶段,选择单元中机器的形成。此阶段的输出已用作第二阶段的输入,以选择最佳数量的运算符。在第一阶段,目标是最大程度地减少物料搬运,搬迁,恒定和变化的机器利用率的总成本,并最大程度地减少同时失衡的机器工作量。在第二阶段,目标是使工人人数最少。第一阶段使用混合粒子群优化(PSO)和epsilon约束进行求解。第二阶段使用Visual Slam进行仿真进行了优化。将结果与GAMS求解器和商用CPLEX求解器进行比较。

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