Solving the distributed two machine flow-shop scheduling problem using differential evolution

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Abstract

Flow-shop scheduling covers a class of widely studied optimisation problem which focus on optimally sequencing a set of jobs to be processed on a set of machines according to a given set of constraints. Recently, greater research attention has been given to distributed variants of this problem. Here we concentrate on the distributed two machine flow-shop scheduling problem (DTMFSP), a special case of classic two machine flow-shop scheduling, with the overall goal of minimising makespan. We apply Differential Evolution to solve the DTMFSP, presenting new best-known results for some benchmark instances from the literature. A comparison to previous approaches from the literature based on the Harmony Search algorithm is also given.

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Dempster, P., Li, P., & Drake, J. H. (2017). Solving the distributed two machine flow-shop scheduling problem using differential evolution. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10385 LNCS, pp. 449–457). Springer Verlag. https://doi.org/10.1007/978-3-319-61824-1_49

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