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Crane scheduling in a shipbuilding environment

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  • Wen, Charlie
  • Eksioglu, Sandra Duni
  • Greenwood, Allen
  • Zhang, Shu

Abstract

This paper describes exact and heuristic approaches for scheduling multiple cranes that service a shipyard that produces multiple ships concurrently. Cranes transport a variety of materials over a shared network of tracks; therefore, inter-crane interference is a major factor affecting makespan and crane utilization. The exact approach models the problem as a multi-commodity flow problem with side constraints on a network. The corresponding integer programming formulation is solved using CPLEX. The heuristics proposed decompose the problem in two sub-problems: a scheduling problem that determines the order in which jobs should be performed, and an assignment problem that assigns cranes to jobs. Computational results show that using the Priority/ACO (ant colony optimization) heuristic gives high quality solutions.

Suggested Citation

  • Wen, Charlie & Eksioglu, Sandra Duni & Greenwood, Allen & Zhang, Shu, 2010. "Crane scheduling in a shipbuilding environment," International Journal of Production Economics, Elsevier, vol. 124(1), pages 40-50, March.
    • Handle: RePEc:eee:proeco:v:124:y:2010:i:1:p:40-50
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    References listed on IDEAS

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    1. Rajendran, Chandrasekharan & Ziegler, Hans, 2004. "Ant-colony algorithms for permutation flowshop scheduling to minimize makespan/total flowtime of jobs," European Journal of Operational Research, Elsevier, vol. 155(2), pages 426-438, June.
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    5. T'kindt, Vincent & Monmarche, Nicolas & Tercinet, Fabrice & Laugt, Daniel, 2002. "An Ant Colony Optimization algorithm to solve a 2-machine bicriteria flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 142(2), pages 250-257, October.
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    Citations

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    Cited by:

    1. Yu-Hsin Chen, Gary, 2013. "A new data structure of solution representation in hybrid ant colony optimization for large dynamic facility layout problems," International Journal of Production Economics, Elsevier, vol. 142(2), pages 362-371.
    2. Li, Wenkai & Goh, Mark & Wu, Yong & Petering, M.E.H. & de Souza, R. & Wu, Y.C., 2012. "A continuous time model for multiple yard crane scheduling with last minute job arrivals," International Journal of Production Economics, Elsevier, vol. 136(2), pages 332-343.
    3. Zhang, Xiaoju & Zeng, Qingcheng & Sheu, Jiuh-Biing, 2019. "Modeling the productivity and stability of a terminal operation system with quay crane double cycling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 181-197.
    4. Kaveshgar, Narges & Huynh, Nathan, 2015. "Integrated quay crane and yard truck scheduling for unloading inbound containers," International Journal of Production Economics, Elsevier, vol. 159(C), pages 168-177.
    5. Lee, Byung Kwon & Kim, Kap Hwan, 2010. "Comparison and evaluation of various cycle-time models for yard cranes in container terminals," International Journal of Production Economics, Elsevier, vol. 126(2), pages 350-360, August.
    6. Boysen, Nils & Briskorn, Dirk & Meisel, Frank, 2017. "A generalized classification scheme for crane scheduling with interference," European Journal of Operational Research, Elsevier, vol. 258(1), pages 343-357.
    7. Zhang, Xiaoju & Zeng, Qingcheng & Yang, Zhongzhen, 2016. "Modeling the mixed storage strategy for quay crane double cycling in container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 171-187.
    8. Batur, G. Didem & Karasan, Oya Ekin & Akturk, M. Selim, 2012. "Multiple part-type scheduling in flexible robotic cells," International Journal of Production Economics, Elsevier, vol. 135(2), pages 726-740.

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