A Memetic Algorithm With A Variable Block Insertion Heuristic for Single Machine Total Weighted Tardiness Problem with Sequence Dependent Setup Times
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Date
2016
Authors
M. Fatih Tasgetiren
Quan-Ke Pan
Yucel Ozturkoglu
Angela H. L. Chen
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IEEE
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Abstract
In this paper a memetic algorithm with a variable block insertion heuristic is presented to solve the single machine total weighted tardiness problem with sequence dependent setup times. Together with the traditional insertion neighborhood structure the memetic algorithm is combined with a variable block insertion heuristic in which a block of jobs are removed from a sequence and then inserted into all possible positions of the partial sequence. For this purpose we devise a variable neighborhood descent algorithm to incorporate different block insertion heuristics having different block sizes. We also employ a simulated annealing type of acceptance criterion to diversify the population. To evaluate its performance the memetic algorithm is tested on a set of benchmark instances from the literature. The analyses of experimental results have shown highly effective performance of the memetic algorithm against the best performing algorithms from the literature. The proposed memetic algorithm was able to find 98 out 120 optimal solutions within reasonable CPU times.
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Keywords
Single machine total weighted tardiness problem with sequence dependent setup times, block insertion heuristic, variable neighborhood search, ruin and recreate procedure, MINIMIZING TOTAL TARDINESS, ITERATED GREEDY ALGORITHM, SCHEDULING PROBLEM, NEIGHBORHOOD SEARCH, BOUND ALGORITHM, PATH RELINKING, LOCAL SEARCH, OPTIMIZATION, PROCESSOR, BRANCH
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Source
IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI)
