An adaptive tabu search approach to JIT sequencing with variable processing times and sequence-dependent setups

An adaptive tabu search approach to JIT sequencing with variable processing times and sequence-dependent setups

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Article ID: iaor19992863
Country: Netherlands
Volume: 109
Issue: 1
Start Page Number: 142
End Page Number: 159
Publication Date: Aug 1998
Journal: European Journal of Operational Research
Authors: ,
Keywords: heuristics
Abstract:

This paper addresses a single machine sequencing problem with variable processing times and sequence-dependent setups. The objective is to find the best trade-off between the JIT goal and the processing time compression and extension costs by simultaneously determining the job sequence and processing times for concerned jobs. Due to the combinatorial nature of the problem, it cannot be optimally solved in polynomial time. A tabu search approach is used to provide good and quick solutions. To improve the computational efficiency, an adaptive neighbourhood generation method is proposed and used in the tabu search algorithm. A total of 100 problems of different sizes have been solved to test the proposed approach. Our computational experience shows that the adaptive approach outperforms several other neighbourhood generation methods in terms of both convergence rate and solution quality. The effects of the search parameters are also discussed.

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