Skip to main content

Robust Optimization Approach to Empty Container Repositioning in Liner Shipping

  • Chapter
  • First Online:
Handbook of Ocean Container Transport Logistics

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 220))

  • 5307 Accesses

Abstract

In global container liner networks, the costly operations of empty container repositioning are necessitated by the imbalance of cargo flows across regions. Up to 40 and 60 % of containers shipped from Europe and North America to Asia are empty, respectively. Repositioning costs are sizable, often amounting up to 5–6 % of a shipping lines revenue. Therefore, identifying an optimal repositioning schedule to rebalance empty containers with minimal cost is one of the most critical planning problems in liner shipping. This is often complicated by the stochastic nature of demand and long transportation lead times. In this paper, we formulate a multiple-stage stochastic programming problem for the optimal repositioning of containers for a liner shipping network. As the problem is highly complex, the stochastic programming formulation is not computationally tractable. Therefore, we utilize emerging techniques in robust optimization to provide a tight approximation (bond) on the stochastic version of the problem. The resulting formulation is a second-order cone program (SOCP) and is computationally tractable. With this approximation, we perform computational experiments to evaluate the effectiveness of different repositioning policies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Agarwal, R., & Ergun, O. (2008). Ship scheduling and network design for cargo routing in liner shipping. Transportation Science, 42(2),175–196.

    Article  Google Scholar 

  • Ang, M., Lim, Y. F., & Sim, M. (2012). Robust storage assignment in unit-load warehouses. Management Science, 58, 2114–2130.

    Article  Google Scholar 

  • Ben-Tal, A., Goryashko, A., Guslitzer, E., & Nemirovski, A. (2004). Adjustable robust solutions of uncertain linear programs. Mathematical Programming, 99, 351–376.

    Article  Google Scholar 

  • Ben-Tal, A., Golany, B., Nemirovski, A., & Vial, J. P. (2005). Retailer-supplier flexible commitments contracts: A robust optimization approach. Manufacturing & Service Operations Management, 7(3), 248–271.

    Article  Google Scholar 

  • Chen, W., & Sim, M. (2007). Goal-driven optimization. Operations Research, 57(2), 342–357.

    Article  Google Scholar 

  • Chen, X., & Zhang, Y. (2009). Uncertain linear programs: Extended affinely adjustable robust counterparts. Operations Research, 57(6), 1469–1482.

    Google Scholar 

  • Chen, X., Sim, M., & Sun, P. (2007). A robust optimization perspective on stochastic programming. Operations Research, 55(6), 1058–1071.

    Article  Google Scholar 

  • Chen, X., Sim, M., Sun, P., & Zhang, J. (2008). A linear decision-based approximation approach to stochastic programming. Operations Research, 56(2), 344–357.

    Article  Google Scholar 

  • Cheung, R. K., & Chen, C. Y. (1998). A two-stage stochastic network model and solution methods for the dynamic empty container allocation problem. Transportation Science, 32 (2), 142–162.

    Article  Google Scholar 

  • Cimino, A., Diaz, R., Longo, F., & Mirabelli, G. (2010). Empty containers repositioning: A state of the art overview. Proceedings of the Spring Simulation Multi-Conference.

    Google Scholar 

  • Crainic, T. G., Gendreau, M., & Dejax, P. (1993). Dynamic and stochastic-models for the allocation of empty containers. Operations Research, 41, 102–126.

    Article  Google Scholar 

  • Dejax, P. J., & Crainic, T. G. (1987). A review of empty flows and fleet management flows in freight transportation. Transportation Science, 21(4), 227–247.

    Article  Google Scholar 

  • Dong, J. X., & Song, D. P. (2009). Container fleet sizing and empty repositioning in liner shipping systems. Transportation Research Part E, 45(6), 860–877.

    Google Scholar 

  • Dyer, M., & Stougie, L. (2006). Computational complexity of stochastic programming problems. Mathematical Programming Series A, 106, 423–432.

    Article  Google Scholar 

  • Erera, A. L., Morales, J. C., & Savelsbergh, M. (2009). Robust optimization for empty repositioning problems. Operations Research, 57(2), 468–483.

    Article  Google Scholar 

  • Francesco, M. D., Crainic, T. G., & Zuddas, P. (2009). The effect of multi-scenario policies on empty container repositioning. Transportation Research Part E, 45, 758–770.

    Article  Google Scholar 

  • Francesco, M. D., Lai, M., & Zuddas, P. (2013). Maritime repositioning of empty containers under uncertain port disruption. Computers & Industrial Engineering, 64, 827–837.

    Article  Google Scholar 

  • Goh, J., & Sim, M. (2010). Distributionally robust optimization and its tractable approximations. Operations Research\textit, 58(4), 902–917.

    Google Scholar 

  • International Maritime Organization. (2012). International Shipping Facts and Figures V Information Resources on Trade, Safety, Security, Environment.

    Google Scholar 

  • Lam, S. W., Lee, L. H., & Tang, L. C. (2007). An approximate dynamic programming approach for the empty container allocation problem. Transportation Research, Part C, 265–277.

    Article  Google Scholar 

  • Levi, R., Perakis, G., & Uichanco, J. (2011). The data-driven newsvendor problem - new bounds and insight. Working Paper, Massachusetts Institute of Technology.

    Google Scholar 

  • Liu, C., Jiang,Z., Chen, F., Liu, X., Liu, L., & Xu, Z. (2010). Empty container repositioning - A review. Proceedings of the 8th World Congress on Intelligent Control and Automation.

    Google Scholar 

  • Meng, Q., Wang, S., Andersson, H., & Thun, K. (2013). Containership routing and scheduling in liner shipping: Overview and future research directions. Transportation Science, Article in Advance

    Google Scholar 

  • New York Times. (29. January 2006). China trade unbalances shipping.

    Google Scholar 

  • See, C. T., & Sim, M. (2010). Robust approximation to multiperiod inventory management. Operations Research, 58(3), 583–594.

    Article  Google Scholar 

  • Song, D. P. (2005). Optimal threshold control of empty vehicle redistribution in two depot service systems. IEEE Trans. On Automatic Control, 50(1), 87–90.

    Article  Google Scholar 

  • Song, D. P., & Carter, J. (2009). Empty container repositioning in shipping industry. Maritime Policy & Management, 36(4), 291–307.

    Article  Google Scholar 

  • Song, D. P., & Dong, J. X. (2008). Empty container management in cyclic shipping routes. Maritime Economics & Logistics, 10, 335–361.

    Article  Google Scholar 

  • Song, D. P., & Dong, J. X. (2012). Cargo routing and empty container repositioning in multiple shipping service routes. Transportation Research Part B, 46, 1556–1575.

    Article  Google Scholar 

  • Song, D. P., & Dong, J. X. (2015). Empty Container Repositioning. In C.-Y., Lee & Q., Meng (Eds.), Handbook of Ocean Container Transport Logistics. Springer.

    Google Scholar 

  • Song, D. P., & Earl, C. F. (2008). Optimal empty vehicle repositioning and fleet-sizing for two-depot services systems. European Journal of Operational Research, 185, 760–777.

    Google Scholar 

  • Song, D. P. , Dinwoodie, J. ,& Roe, M. (2007).Integrated vehicle fleet-sizing, leasing and dispatching policy in a shuttle service system.International Journal of Logistics Research and Applications, 10(1), 29–40.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ho-Tak Tsang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Tsang, HT., Mak, HY. (2015). Robust Optimization Approach to Empty Container Repositioning in Liner Shipping. In: Lee, CY., Meng, Q. (eds) Handbook of Ocean Container Transport Logistics. International Series in Operations Research & Management Science, vol 220. Springer, Cham. https://doi.org/10.1007/978-3-319-11891-8_7

Download citation

Publish with us

Policies and ethics