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Mixed model disassembly line balancing problem with fuzzy goals

机译:具有模糊目标的混合模型拆卸线平衡问题

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The collection of used products is the driving force of remanufacturing systems and enterprises can gain significant economic, technical and social benefits from recycling. All products are disassembled up to some level in remanufacturing systems. The best way to disassemble returned products is valid by a well-balanced disassembly line. In this paper, a mixed integer programming (MIP) model is proposed for a mixed model disassembly line balancing (MMDLB) problem with multiple conflicting objectives: (1) minimising the cycle time, (2) minimising the number of disassembly workstations and (3) providing balanced workload per workstation. In most real world MMDLB problems, the targeted goals of decision makers are frequently imprecise or fuzzy because some information may be incomplete and/or unavailable over the planning horizon. This study is the first in the literature to offer the binary fuzzy goal programming (BFGP) and the fuzzy multi-objective programming (FMOP) approaches for the MMDLB problem in order to take into account the vague aspirations of decision makers. An illustrative example based on two industrial products is presented to demonstrate the validity of the proposed models and to compare the performances of the BFGP and the FMOP approaches.
机译:旧产品的收集是再制造系统的驱动力,企业可以从回收中获得重大的经济,技术和社会效益。在再制造系统中,所有产品的拆卸程度均达到一定水平。最好的平衡拆解生产线的方法是有效的拆解生产线。本文针对具有多个冲突目标的混合模型拆卸线平衡(MMDLB)问题,提出了一种混合整数规划(MIP)模型:(1)最小化周期时间,(2)最小化拆卸工作站的数量,以及(3) )为每个工作站提供均衡的工作负载。在大多数现实世界中的MMDLB问题中,决策者的目标目标经常是不精确或模糊的,因为某些信息在计划范围内可能不完整和/或不可用。这项研究是文献中第一个针对MMDLB问题提供二进制模糊目标规划(BFGP)和模糊多目标规划(FMOP)方法的方法,目的是考虑决策者的模糊愿望。给出了一个基于两种工业产品的说明性例子,以证明所提出模型的有效性,并比较了BFGP和FMOP方法的性能。

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