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https://hdl.handle.net/11499/7942
Title: | Mixed model disassembly line balancing problem with fuzzy goals | Authors: | Paksoy, T. Güngör, Aşkıner Özceylan, E. Hancılar, Arif |
Keywords: | Binary fuzzy goal programming Disassembly line balancing Fuzzy multi-objective programming Mixed integer programming Mixed model disassembly lines Disassembly line Multiobjective programming Computer programming Decision making |
Abstract: | 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. © 152013 © 2013 Taylor & Francis. | URI: | https://hdl.handle.net/11499/7942 https://doi.org/10.1080/00207543.2013.795251 |
ISSN: | 0020-7543 |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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