Abstract
Traditionally, the yard-planning problem has been considered to be the assignment of yard spaces to arriving vessels in practices of container terminals. This study proposes an integrated decision-making framework for the yard-planning that simultaneously considers various resources such as storage space, yard cranes, and traffic area in container terminals for planning. The decision-making framework in this study is based on a mathematical model, which supports intelligent yard-planning activities considering work-loads on various related resources. Further, it is shown that the decision-making framework for the yard-planning can be extended to that for simultaneous decisions on yard plans and handling capacity of yard cranes per block. A heuristic algorithm is also proposed in order to reduce the computational time for planning. Numerical experiments are conducted to validate the models and algorithms proposed in this study.
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References
Cao B., Uebe G. (1995) Solving transportation problems with nonlinear side constraints with tabu search. Computers and Operations Research 22: 593–603
Choe R., Park T., Oh M.-S., Kang J., Ryu K.R. (2011) Generating a rehandling-free intra-block remarshaling plan for an automated container yard. Journal of Intelligent Manufacturing, on-line available 22: 201–217
Chung R. K., Li C., Lin W. (2002) Interblock crane deployment in container terminals. Transportation Science 36: 79–93
Cordeau J. F., Gaudioso M., Laporte G., Moccia L. (2007) The service allocation problem at the Gioia Tauro maritime terminal. European Journal of Operational Research 176: 1167–1184
Han Y., Lee L. H., Chew E. P., Tan K. C. (2008) A yard storage strategy for minimizing traffic congestion in a marine container transshipment hub. OR Spectrum 30: 697–720
Kang J., Ryu K., Kim K. (2006) Deriving stacking strategies for export containers with uncertain weight information. Journal of Intelligent Manufacturing 17: 399–410
Kim K. H., Park K. T. (2003) Dynamic space allocation for temporary storage. International Journal of Systems Science 34: 11–20
Kozan E. (2000) Optimising container transfers at multimodal terminals. Mathematical and Computer Modelling 31: 235–243
Lee L. H., Chew E. P., Tan K. C., Han Y. (2006) An optimization model for storage yard management in transshipment hubs. OR Spectrum 28: 539–561
Linn R., Zhang C. (2003) A heuristic for dynamic yard crane deployment in a container terminal. IIE Transactions 35: 161–174
Linn R., Liu J., Wan Y., Zhang C., Murty K.G. (2003) Rubber tired gantry crane deployment for container yard operation. Computers and Industrial Engineering 45: 429–442
Petering M. E. H., Murty K. G. (2009) Effect of block length and yard crane deployment systems on overall performance at a seaport container transshipment terminal. Computers and Operations Research 36: 1711–1725
Taleb-Ibrahimi M., de Castilho B., Daganzo C. F. (1993) Storage space vs handling work in container terminals. Transportation Research Part B 27: 13–32
Zhang C., Liu J., Wan Y., Murty K. G., Linn R. J. (2003) Storage space allocation in container terminals. Transportation Research Part B 37: 883–903
Zhang C., Wan Y., Liu J., Linn R. J. (2002) Dynamic crane deployment in container storage yards. Transportation Research Part B 36: 537–555
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Won, S.H., Zhang, X. & Kim, K.H. Workload-based yard-planning system in container terminals. J Intell Manuf 23, 2193–2206 (2012). https://doi.org/10.1007/s10845-011-0565-x
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DOI: https://doi.org/10.1007/s10845-011-0565-x