Solution method for a large-scale loom scheduling problem with machine eligibility and splitting property
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Date
2017-04-03
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Taylor & Francis
Abstract
In this paper, we focused on a real-life, large-scale problem of loom scheduling, which has 1100 independent jobs and 133 unrelated parallel machines with machine eligibility constraint. The authors focused on the scheduling problems that includes sequence-dependent setup times and the job splitting property to minimize the makespan. An adapted version of hybrid genetic algorithm in this study, incorporated a machine eligibility constraint. Adding this constraint complicated the problem, but doing so is compulsory to solve a real-life problem. To simplify the problem, we used the typesetting structure of the weaving industry. Utilizing random key numbers provided feasible chromosomes for each generation. Flexible chromosome structures and local search adaptation into the genetic algorithm were some of the other factors that allowed us to improve the makespan by up to 14% in this application.
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Keywords
Materials science, Genetic algorithms, Large-scale problem, Loom, Scheduling, Sequence-dependent setup, Genetic-algorithm, Parallel machines, Programming approach, Minimizing makespan, Times, Jobs, Restrictions, Constraints, Algorithms, Chromosomes, Looms, Problem solving, Genetic algorithms, Optimization, Textile industry, Chromosome structure, Hybrid genetic algorithms, Large-scale problem, Machine eligibility, Machine eligibility constraint, Scheduling problem, Sequence-dependent setup time, Unrelated parallel machines, Job shop scheduling
Citation
Eroğlu, D. Y. ve Özmutlu, H. C. (2017). ''Solution method for a large-scale loom scheduling problem with machine eligibility and splitting property''. Journal of the Textile Institute, 108(12), 2154-2165.