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Modeling and solution for the ship stowage planning problem of coils in the steel industry

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  • Lixin Tang
  • Jiyin Liu
  • Fei Yang
  • Feng Li
  • Kun Li

Abstract

We consider a ship stowage planning problem where steel coils with known destination ports are to be loaded onto a ship. The coils are to be stowed on the ship in rows. Due to their heavy weight and cylindrical shape, coils can be stowed in at most two levels. Different from stowage problems in previous studies, in this problem there are no fixed positions on the ship for the coils due to their different sizes. At a destination port, if a coil to be unloaded is not at a top position, those blocking it need to be shuffled. In addition, the stability of ship has to be maintained after unloading at each destination port. The objective for the stowage planning problem is to minimize a combination of ship instability throughout the entire voyage, the shuffles needed for unloading at the destination ports, and the dispersion of coils to be unloaded at the same destination port. We formulate the problem as a novel mixed integer linear programming model. Several valid inequalities are derived to help reducing solution time. A tabu search (TS) algorithm is developed for the problem with the initial solution generated using a construction heuristic. To evaluate the proposed TS algorithm, numerical experiments are carried out on problem instances of three different scales by comparing it with a model‐based decomposition heuristic, the classic TS algorithm, the particle swarm optimization algorithm, and the manual method used in practice. The results show that for small problems, the proposed algorithm can generate optimal solutions. For medium and large practical problems, the proposed algorithm outperforms other methods. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 564–581, 2015

Suggested Citation

  • Lixin Tang & Jiyin Liu & Fei Yang & Feng Li & Kun Li, 2015. "Modeling and solution for the ship stowage planning problem of coils in the steel industry," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(7), pages 564-581, October.
  • Handle: RePEc:wly:navres:v:62:y:2015:i:7:p:564-581
    DOI: 10.1002/nav.21664
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    References listed on IDEAS

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    1. Imai, Akio & Sasaki, Kazuya & Nishimura, Etsuko & Papadimitriou, Stratos, 2006. "Multi-objective simultaneous stowage and load planning for a container ship with container rehandle in yard stacks," European Journal of Operational Research, Elsevier, vol. 171(2), pages 373-389, June.
    2. Mordecai Avriel & Michal Penn & Naomi Shpirer & Smadar Witteboon, 1998. "Stowage planning for container ships to reduce the number of shifts," Annals of Operations Research, Springer, vol. 76(0), pages 55-71, January.
    3. Nowicki, Eugeniusz & Smutnicki, Czeslaw, 1998. "The flow shop with parallel machines: A tabu search approach," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 226-253, April.
    4. Lixin Tang & Wei Jiang & Jiyin Liu & Yun Dong, 2015. "Research into container reshuffling and stacking problems in container terminal yards," IISE Transactions, Taylor & Francis Journals, vol. 47(7), pages 751-766, July.
    5. Lixin Tang & Gongshu Wang & Zhi-Long Chen, 2014. "Integrated Charge Batching and Casting Width Selection at Baosteel," Operations Research, INFORMS, vol. 62(4), pages 772-787, August.
    6. Sciomachen, Anna & Tanfani, Elena, 2007. "A 3D-BPP approach for optimising stowage plans and terminal productivity," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1433-1446, December.
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    Cited by:

    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. 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).
    3. Tanaka, Shunji & Tierney, Kevin & Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon & Ruiz, Rubén, 2019. "A branch and bound approach for large pre-marshalling problems," European Journal of Operational Research, Elsevier, vol. 278(1), pages 211-225.
    4. Pfrommer, Jakob & Meyer, Anne & Tierney, Kevin, 2024. "Solving the unit-load pre-marshalling problem in block stacking storage systems with multiple access directions," European Journal of Operational Research, Elsevier, vol. 313(3), pages 1054-1071.

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