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Scheduling of steelmaking-continuous casting process with different processing routes using effective surrogate Lagrangian relaxation approach and improved concave–convex procedure

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  • Haijuan Cui
  • Xiaochuan Luo
  • Yuan Wang

Abstract

This paper studies a steelmaking-continuous casting scheduling problem with different processing routes. We model this problem as a mixed-integer nonlinear programming problem. Next, Lagrangian relaxation approach is introduced to solve this problem by relaxing the coupling constraints. Due to the nonseparability in Lagrangian functions, we design an improved concave–convex procedure to decompose the Lagrangian relaxation problem into three tractable subproblems and analyse the convergence of the improved concave–convex procedure under some assumptions. Furthermore, we present an effective surrogate subgradient algorithm with global convergence to solve the Lagrangian dual problem. Lastly, computational experiments on the practical production data show the effectiveness of the proposed surrogate subgradient method for solving this steelmaking-continuous casting scheduling problem.

Suggested Citation

  • Haijuan Cui & Xiaochuan Luo & Yuan Wang, 2022. "Scheduling of steelmaking-continuous casting process with different processing routes using effective surrogate Lagrangian relaxation approach and improved concave–convex procedure," International Journal of Production Research, Taylor & Francis Journals, vol. 60(11), pages 3435-3460, June.
    • Handle: RePEc:taf:tprsxx:v:60:y:2022:i:11:p:3435-3460
    DOI: 10.1080/00207543.2021.1924408
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