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Optimal operating strategy for a long-haul liner service route


  • Meng, Qiang
  • Wang, Shuaian


This paper proposes an optimal operating strategy problem arising in liner shipping industry that aims to determine service frequency, containership fleet deployment plan, and sailing speed for a long-haul liner service route. The problem is formulated as a mixed-integer nonlinear programming model that cannot be solved efficiently by the existing solution algorithms. In view of some unique characteristics of the liner shipping operations, this paper proposes an efficient and exact branch-and-bound based [epsilon]-optimal algorithm. In particular, a mixed-integer nonlinear model is first developed for a given service frequency and ship type; two linearization techniques are subsequently presented to approximate this model with a mixed-integer linear program; and the branch-and-bound approach controls the approximation error below a specified tolerance. This paper further demonstrates that the branch-and-bound based [epsilon]-optimal algorithm obtains a globally optimal solution with the predetermined relative optimality tolerance [epsilon] in a finite number of iterations. The case study based on an existing long-haul liner service route shows the effectiveness and efficiency of the proposed solution method.

Suggested Citation

  • Meng, Qiang & Wang, Shuaian, 2011. "Optimal operating strategy for a long-haul liner service route," European Journal of Operational Research, Elsevier, vol. 215(1), pages 105-114, November.
  • Handle: RePEc:eee:ejores:v:215:y:2011:i:1:p:105-114

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    References listed on IDEAS

    1. Kim, Dong-Guen & Kim, Yeong-Dae, 2010. "A branch and bound algorithm for determining locations of long-term care facilities," European Journal of Operational Research, Elsevier, vol. 206(1), pages 168-177, October.
    2. B. J. Powell & A .N. Perkins, 1997. "Fleet deployment optimization for liner shipping: an integer programming model," Maritime Policy & Management, Taylor & Francis Journals, vol. 24(2), pages 183-192, January.
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    6. Bert Vernimmen & Wout Dullaert & Steve Engelen, 2007. "Schedule Unreliability in Liner Shipping: Origins and Consequences for the Hinterland Supply Chain," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 9(3), pages 193-213, September.
    7. Xiaofeng, Hu & Erfei, Wu & Jinsong, Bao & Ye, Jin, 2010. "A branch-and-bound algorithm to minimize the line length of a two-sided assembly line," European Journal of Operational Research, Elsevier, vol. 206(3), pages 703-707, November.
    8. Besar, D. & Booth, P. & Chan, K. K. & Milne, A. K. L. & Pickles, J., 2011. "Systemic Risk in Financial Services," British Actuarial Journal, Cambridge University Press, vol. 16(2), pages 195-300, November.
    9. Ronen, David, 1993. "Ship scheduling: The last decade," European Journal of Operational Research, Elsevier, vol. 71(3), pages 325-333, December.
    10. H N Psaraftis, 2005. "EU Ports Policy: Where do we Go from Here?," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 7(1), pages 73-82, March.
    11. Notteboom, Theo E. & Vernimmen, Bert, 2009. "The effect of high fuel costs on liner service configuration in container shipping," Journal of Transport Geography, Elsevier, vol. 17(5), pages 325-337.
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