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An iterated greedy matheuristic for scheduling in steelmaking-continuous casting process

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  • Juntaek Hong
  • Kyungduk Moon
  • Kangbok Lee
  • Kwansoo Lee
  • Michael L. Pinedo

Abstract

Steelmaking-Continuous Casting (SCC) is a bottleneck in the steel production process and its scheduling has become more challenging over time. In this paper, we provide an extensive literature review that highlights challenges in the SCC scheduling and compares existing solution methods. From the literature review, we collect the essential features of an SCC process, such as unrelated parallel machine environments, stage skipping, and maximum waiting time limits in between successive stages. We consider an SCC scheduling problem with as objective the minimisation of the weighted sum of cast break penalties, total waiting time, total earliness, and total tardiness. We formulate the problem as a mixed-integer linear programming model and develop an iterated greedy matheuristic that solves its subproblems to find a near-optimal solution. Through numerical experiments, we show that our algorithm outperforms two types of genetic algorithms when applied to test instances.

Suggested Citation

  • Juntaek Hong & Kyungduk Moon & Kangbok Lee & Kwansoo Lee & Michael L. Pinedo, 2022. "An iterated greedy matheuristic for scheduling in steelmaking-continuous casting process," International Journal of Production Research, Taylor & Francis Journals, vol. 60(2), pages 623-643, January.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:2:p:623-643
    DOI: 10.1080/00207543.2021.1975839
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