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A multi-objective integrated cellular manufacturing systems design with dynamic system reconfiguration

机译:动态系统重构的多目标集成蜂窝制造系统设计

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摘要

Cellular manufacturing system (CMS)-an important application of group technology-has been recognized as an effective way to enhance the productivity in a factory. As a result of dynamic deterministic demands within the planning horizon, a CMS configuration for a period might not be optimal or even feasible for other planning periods. Consequently, a multi-objective dynamic cell formation problem is presented, where the total cells load variation and sum of the miscellaneous costs are to be minimized simultaneously. The second objective function calculates machine costs, internal part production, intercellular and intracellular material handling, back order, inventory holding and subcontracting. Since in this type of problem, objectives are in conflict with each other, finding an ideal solution (a solution which satisfies all objectives simultaneously) is not possible. Therefore a non-dominated sorting genetic algorithm (NSGAII) is designed for finding Pareto-optimal frontier that decision maker can select her/his slightly solution. Numerical examples have been solved for demonstrate the efficiency of the proposed algorithm.
机译:蜂窝制造系统(CMS)-组技术的重要应用-已被公认为是提高工厂生产率的有效方法。由于计划范围内的动态确定性需求,一个期间的CMS配置对于其他计划期间可能不是最佳的,甚至不可行。因此,提出了多目标动态小区形成问题,其中总小区负载变化和杂项成本之和要同时最小化。第二个目标函数计算机器成本,内部零件生产,细胞间和细胞内材料处理,延期交货,库存持有和分包。由于在这种类型的问题中,目标彼此冲突,因此不可能找到理想的解决方案(同时满足所有目标的解决方案)。因此,设计了一种非支配的排序遗传算法(NSGAII),以查找决策者可以选择其轻微解决方案的帕累托最优边界。数值例子已经解决,以证明所提出算法的效率。

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