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    A hybrid scatter search method for solving fuzzy no-wait flow-shop scheduling problems
    (Taylor and Francis Ltd., 2024) Başar, Ramazan; Engin, Orhan
    The literature published since the year 2000 was reviewed regarding the no-wait flow-shop scheduling (No-WFSS) problem. The No-WFSS problem with separate set-up times and fuzzy due dates is addressed to maximize the customer satisfaction index. A scatter search algorithm (SSA) is proposed, hybridized by some operators. The proposed SSA was first used for solving the considered fuzzy no-wait flow-shop scheduling with set-up time (FNo-WFSSWST) problem. Parameters were calibrated using 192 No-WFSS benchmark instances. The proposed SSA was compared with the genetic heuristic, adaptive learning approach, and hybrid ant colony optimization methods from the literature, showing significant performance improvements. It is concluded that the proposed algorithm is an efficient method for solving FNo-WFSSWST problems.
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    Öğe
    Distributed no-wait flow shop with fuzzy environment
    (Springer Science and Business Media Deutschland GmbH, 2022) Başar, Ramazan; Büyüközkan, Kadir; Engin, Orhan
    In the no-wait flow shop scheduling problem, n-job should be proceeded on m-machine with the same order and do not permit the jobs to wait during the scheduling periods. Also, at the distributed no-wait flow shop scheduling problem, there are multi-factory for processing n-job with m-machine for no-wait constraint. In this study, distributed no-wit flow shop scheduling with the fuzzy due date is considered. The due date of the jobs is defined with fuzzy numbers. A parallel kangaroo algorithm is proposed to solve the distributed no-wait flow shop scheduling problem with the fuzzy due date. The proposed algorithm is tested from the literature by the benchmark problems. The results show that the proposed parallel kangaroo algorithm is efficient for distributed no-wit flow shop scheduling problems with fuzzy due date problems.