Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 49, Issue 16, Pages 4787-4806Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2010.510486
Keywords
materials handling; neural network applications; multi-criteria decision making; scheduling
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Funding
- National Science Foundation of China [71071115, 70771065, 50905114]
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This paper studies the problem of scheduling a multiple-load carrier subject to last-in-first-out loading constraints in an automobile assembly line. Two scheduling criteria, the throughput of the assembly line and the material handling distance, are considered in order to maximise the profit of the assembly line. Different from other studies, the product mix and weights of the scheduling criteria are considered to be variable. A scheduling approach is proposed for the problem. At moments when the product mix or weights of the scheduling criteria change, the scheduling approach can select an appropriate rule from a set of given rules. In this study, the proposed approach is compared with other approaches by simulation in order to verify the performance of the proposed approach. The results indicate that, when the product mix and weights of the scheduling criteria are variable, the proposed scheduling approach outperforms other approaches.
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