Positioning Empty Containers among Ports Considering Leasing and Purchasing Options Using Robust Optimization

Authors

  • Parsa Tavakoli * Department of Logistics And Supply Chain, Tarbiat Modares University, Tehran, Iran. https://orcid.org/0009-0008-5034-0907
  • Majid Sheikhmohammady Department of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran.
  • Ehsan Nikbakhsh Department of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran. https://orcid.org/0000-0002-5872-9756

https://doi.org/10.48313/scodm.v3i1.49

Abstract

In the competitive shipping industry, container transportation plays a major role. Marine transportation has significantly grown over the past decades, thereby affecting worldwide Trade balances. Empty Container Repositioning (ECR) has always been a serious challenge for carriers and liners. The goal of this study is to propose a model for container carriers and liner companies to improve container transportation between ports and reduce imbalances. This paper presents an optimization model for positioning empty containers among ports, accounting for leasing and purchasing costs, using robust programming. The proposed model's objective is to minimize the relevant costs container carriers often face in the business environment, including transportation, inventory, leasing and purchasing, and handling costs. Results from the developed robust optimization model showed an approximately 70% increase in total cost in the worst-case scenario. Container leasing capacity and vessel size have been modeled using mixed-integer programming and robust optimization in the proposed model.

Keywords:

Container transportation, Empty container positioning, Marine transportation, Mixed integer programming, Robust optimization

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Published

2026-02-14

Issue

Vol. 3 No. 1 (2026): Supply Chain and Operations Decision Making

Section

Articles

How to Cite

Tavakoli, P. ., Sheikhmohammady, M. ., & Nikbakhsh, E. . (2026). Positioning Empty Containers among Ports Considering Leasing and Purchasing Options Using Robust Optimization. Supply Chain and Operations Decision Making, 3(1), 10-25. https://doi.org/10.48313/scodm.v3i1.49

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