A heuristic procedure for the automobile assembly-line sequencing problem considering multiple product options

Mixed-model assembly nowadays is a common practice in the automobile industry. In an automobile assembly plant, many car options often need to be considered in sequencing an assembly line, for example, the multiple sequencing objectives that consider a pattern, blocking, spacing, and smoothing of op...

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Bibliographic Details
Published in:International journal of production research 2008-10, Vol.46 (20), p.5827-5847
Main Authors: Ding, F.-Y., He, J.
Format: Article
Language:English
Subjects:
Applied sciences
Assembly line sequencing
Assembly lines
Automobile industry
Automobile production
Automobiles
Exact sciences and technology
Heuristic
Inventory control, production control. Distribution
Operational research and scientific management
Operational research. Management science
Sequencing considering multiple options
Sequential scheduling
Simulated annealing
Studies
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Summary:Mixed-model assembly nowadays is a common practice in the automobile industry. In an automobile assembly plant, many car options often need to be considered in sequencing an assembly line, for example, the multiple sequencing objectives that consider a pattern, blocking, spacing, and smoothing of options. A general heuristic procedure is developed in this paper for sequencing automobile assembly lines considering multiple options. The procedure obtains an initial sequence by an enhanced constructive procedure, swaps orders for the most deteriorating category of objectives, and performs re-sequencing attempting to improve the swapped sequence. The heuristic procedure was shown to frequently improve the initial sequences by swapping and re-sequencing when swapping opportunities exist. A further improvement step is also proposed to perform a limited search based on the swapped solution. The limited-search improvement step was shown to be effective in further improving solutions from the heuristic procedure in the computational experimentation. Solutions from the heuristic procedure in conjunction with the limited-search improvement step were compared to those from the simulated annealing procedure for large-size problems and showed relatively positive results.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207540701381291