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Minimum cost berth allocation problem in maritime logistics: new mixed integer programming models

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Abstract

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.

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Acknowledgement

The authors are thankful to the reviewer and the Editor for their constructive suggestions and comments to improve the initial version of our manuscript.

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Authors and Affiliations

  1. Department of Management Studies, Indian Institute of Technology Madras, Chennai, 600 036, India

    Bobin Cherian Jos, M Harimanikandan & Chandrasekharan Rajendran

  2. School of Business, Economics and Information Systems, University of Passau, Passau, Germany

    Hans Ziegler

Authors
  1. Bobin Cherian Jos
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  2. M Harimanikandan
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  3. Chandrasekharan Rajendran
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  4. Hans Ziegler
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Correspondence to Chandrasekharan Rajendran.

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Jos, B.C., Harimanikandan, M., Rajendran, C. et al. Minimum cost berth allocation problem in maritime logistics: new mixed integer programming models. Sādhanā 44, 149 (2019). https://doi.org/10.1007/s12046-019-1128-7

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  • DOI: https://doi.org/10.1007/s12046-019-1128-7

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