Minimum cost berth allocation problem in maritime logistics: new mixed integer programming models
The berth allocation problem (BAP) involves decisions on how to allocate the berth space and to sequence maritime vessels that are to be loaded and unloaded at a container terminal involved in the maritime logistics. As the berth is a critical resource in a container terminal, an effective use of it is highly essential to have efficient berthing and servicing of vessels, and to optimize the associated costs. This study focuses on the minimum cost berth allocation problem (MCBAP) at a container terminal where the maritime vessels arrive dynamically. The objective comprises the waiting time penalty, tardiness penalty, handling cost and benefit of early service completion of vessels. This paper proposes three computationally efficient mixed integer linear programming (MILP) models for the MCBAP. Through numerical experiments, the proposed MILP models are compared to an existing model in the literature to evaluate their computational performance. The computational study with problem instances of various problem characteristics demonstrates the computational efficiency of the proposed models.
KeywordsMaritime logistics discrete berth allocation problem minimum cost berth allocation problem mixed integer linear programming models
The authors are thankful to the reviewer and the Editor for their constructive suggestions and comments to improve the initial version of our manuscript.
- 1.UNCTAD (United Nations Conference on Trade and Development) 2018 Review of maritime transport 2018 Google Scholar
- 11.Kovač N, Stanimirović Z and Davidović T 2018 Metaheuristic approaches for the minimum cost hybrid berth allocation problem. In: Konstantopoulos C and Pantziou G (Eds.) Modeling, Computing and Data Handling Methodologies for Maritime Transportation. Cham: Springer, pp. 1–47Google Scholar
- 21.Hansen P and Oguz C 2003 A note on formulations of static and dynamic berth allocation problems. Les Cah du GERAD G-2003-30 HEC MontréalGoogle Scholar