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A decision support flexible scheduling system for continuous galvanization lines using genetic algorithm

  • Production Management
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Abstract

An important, complex problem for logistic optimization in the steel manufacturing plants is obtaining a flexible and adaptive scheduling system for a continuous galvanization line (CGL). The problem tackled in this work involves several constraints and characteristics inspired by real-life manufacturing goals. Given the complexity of the problem, which belongs to the class of NP-hard problems, a genetic algorithm (GA) methodology was developed, combining a penalty procedure defined for constraints with assigned weights for different characteristics of coils. By enlisting the ability and flexibility of GAs, a set of parameters are analyzed to achieve the best results for practical applications. This scheduling solution predicts a CGL sequences with a minimum number of coil transitions, to improve productivity and reduce costs.

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Authors and Affiliations

  1. Braude College of Engineering, Karmiel, Israel

    Miri Weiss Cohen, Hila Foxx & Shimon Ben Alul

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  1. Miri Weiss Cohen
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  2. Hila Foxx
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  3. Shimon Ben Alul
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Correspondence to Miri Weiss Cohen.

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Weiss Cohen, M., Foxx, H. & Ben Alul, S. A decision support flexible scheduling system for continuous galvanization lines using genetic algorithm. Prod. Eng. Res. Devel. 13, 43–52 (2019). https://doi.org/10.1007/s11740-018-0856-6

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  • DOI: https://doi.org/10.1007/s11740-018-0856-6

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