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Metaheuristic Approaches for the Minimum Cost Hybrid Berth Allocation Problem

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Modeling, Computing and Data Handling Methodologies for Maritime Transportation

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 131))

Abstract

The Minimum Cost Hybrid Berth Allocation problem is defined as follows: for a given list of vessels with fixed handling times, the appropriate intervals in berth and time coordinates have to be determined in such a way that the total cost is minimized. The costs are influenced by positioning of vessels, time of berthing, and time of completion for all vessels. Having in mind that the speed of finding high-quality solutions is of crucial importance for designing an efficient and reliable decision support system in container terminal, metaheuristic methods are the obvious choice for solving MCHBAP. In this chapter, we survey Evolutionary Algorithm (EA), Bee Colony Optimization (BCO), and Variable Neighborhood Descent (VND) metaheuristics, and propose General Variable Neighborhood Search (GVNS) approach for MCHBAP. All four metaheuristics are evaluated and compared against each other and against exact solver on real-life and randomly generated instances from the literature. The analysis of the obtained results shows that on instances reflecting real-life situations, all four metaheuristics were able to find optimal solutions in short execution times. The newly proposed GVNS showed to be superior over the remaining three metaheuristics in the sense of running times. Randomly generated instances were out of reach for exact solver, while EA, BCO, VND, and GVNS easily provided high-quality solutions in each run. The results obtained on generated data set show that the newly proposed GVNS outperformed EA, BCO, and VND regarding the running times while preserving the high quality of solutions. The computational analysis indicates that MCHBAP can be successfully addressed by GVNS and we believe that it is applicable to related problems in maritime transportation.

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Acknowledgements

This research was partially supported by Serbian Ministry of Education, Science and Technological Development under the grants nos. 174010 and 174033. The authors would like to thank the anonymous referees for the valuable suggestions that led to the improved presentation of the results described in this manuscript.

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Authors and Affiliations

  1. Maritime Faculty, University of Montenegro, Dobrota 36, 85330, Kotor, Montenegro

    Nataša Kovač

  2. Faculty of Mathematics, University of Belgrade, Studentski trg 16, 11000, Belgrade, Serbia

    Zorica Stanimirović

  3. Mathematical Institute, Serbian Academy of Sciences and Arts, Kneza Mihaila 36/III, 11000, Belgrade, Serbia

    Tatjana Davidović

Authors
  1. Nataša Kovač
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  2. Zorica Stanimirović
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  3. Tatjana Davidović
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Correspondence to Zorica Stanimirović .

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Editors and Affiliations

  1. Department of Informatics, University of Piraeus, Piraeus, Greece

    Charalampos Konstantopoulos

  2. Department of Informatics, Technological Educational Institute of Athens, Athens, Greece

    Grammati Pantziou

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Kovač, N., Stanimirović, Z., Davidović, T. (2018). Metaheuristic Approaches for the Minimum Cost Hybrid Berth Allocation Problem. In: Konstantopoulos, C., Pantziou, G. (eds) Modeling, Computing and Data Handling Methodologies for Maritime Transportation. Intelligent Systems Reference Library, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-319-61801-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-61801-2_1

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