Mixed model disassembly line balancing problem with fuzzy goals

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 val...

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Veröffentlicht in:International journal of production research Jg. 51; H. 20; S. 6082 - 6096
Hauptverfasser: Paksoy, Turan, Güngör, Aşkıner, Özceylan, Eren, Hancilar, Arif
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Taylor & Francis 15.10.2013
Taylor & Francis LLC
Schlagworte:
Assembly lines
binary fuzzy goal programming
Decision making
Disassembly
disassembly line balancing
Dismantling
Fuzzy
Fuzzy logic
fuzzy multi-objective programming
Fuzzy set theory
Goal programming
Integer programming
mixed integer programming
mixed model disassembly lines
Remanufacturing
Studies
Workstations
ISSN:0020-7543, 1366-588X
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Zusammenfassung: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.
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ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2013.795251