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Models and algorithms for shuffling problems in steel plants

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  • Lixin Tang
  • Ren Zhao
  • Jiyin Liu

Abstract

In this article, we study item shuffling (IS) problems arising in the logistics system of steel production. An IS problem here is to optimize shuffling operations needed in retrieving a sequence of steel items from a warehouse served by a crane. There are two types of such problems, plate shuffling problems (PSP) and coil shuffling problems (CSP), considering the item shapes. The PSP is modeled as a container storage location assignment problem. For CSP, a novel linear integer programming model is formulated considering the practical stacking and shuffling features. Several valid inequalities are constructed to accelerate the solving of the models. Some properties of optimal solutions of PSP and CSP are also derived. Because of the strong NP‐hardness of the problems, we consider some special cases of them and propose polynomial time algorithms to obtain optimal solutions for these cases. A greedy heuristic is proposed to solve the general problems and its worst‐case performances on both PSP and CSP are analyzed. A tabu search (TS) method with a tabu list of variable length is proposed to further improve the heuristic solutions. Without considering the crane traveling distance, we then construct a rolling variable horizon heuristic for the problems. Numerical experiments show that the proposed heuristic algorithms and the TS method are effective. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012

Suggested Citation

  • Lixin Tang & Ren Zhao & Jiyin Liu, 2012. "Models and algorithms for shuffling problems in steel plants," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(7), pages 502-524, October.
  • Handle: RePEc:wly:navres:v:59:y:2012:i:7:p:502-524
    DOI: 10.1002/nav.21503
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    References listed on IDEAS

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    1. Emrah B. Edis & Ozlem Uzun Araz & Ozgur Eski & Rahime Sancar Edis, 2023. "Storage location assignment of steel coils in a manufacturing company: an integer linear programming model and a greedy randomized adaptive search procedure," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 67-109, April.
    2. Ruiyou Zhang & Shixin Liu & Herbert Kopfer, 2016. "Tree search procedures for the blocks relocation problem with batch moves," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 397-424, September.
    3. Lanza, Giacomo & Passacantando, Mauro & Scutellà, Maria Grazia, 2022. "Assigning and sequencing storage locations under a two level storage policy: Optimization model and matheuristic approaches," Omega, Elsevier, vol. 108(C).
    4. M. Hakan Akyüz & Chung‐Yee Lee, 2014. "A mathematical formulation and efficient heuristics for the dynamic container relocation problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(2), pages 101-118, March.
    5. Marolt Jakob & Lerher Tone, 2018. "Comparison of Lowest-Slot and Nearest-Stack Heuristics for Storage Assignment of Steel Bar Sets," Logistics, Supply Chain, Sustainability and Global Challenges, Sciendo, vol. 9(2), pages 37-45, October.
    6. David Boywitz & Nils Boysen & Dirk Briskorn, 2016. "Resequencing with parallel queues to minimize the maximum number of items in the overflow area," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(5), pages 401-415, August.

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