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A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms

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Book cover Operations Research and Enterprise Systems (ICORES 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 577))

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Abstract

Tug fleet optimisation algorithms can be designed to solve the problem of dynamically positioning a fleet of tugs in order to mitigate the risk of oil tanker drifting accidents. In this paper, we define the 1D tug fleet optimisation problem and present a receding horizon genetic algorithm for solving it. The algorithm can be configured with a set of cost functions such that each configuration effectively constitute a unique tug fleet optimisation algorithm. To measure the performance, or merit, of such algorithms, we propose two evaluation heuristics and test them by means of a computational simulation study. Finally, we discuss our findings and some of our related work on a parallel implementation and an alternative 2D nonlinear mixed integer programming formulation of the problem.

Robin T. Bye—This paper is an extended and revised version of a paper presented at the 4th International Conference on Operations Research and Enterprise Systems (ICORES’15) in Lisbon, Portugal, January 2015 [1].

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Notes

  1. 1.

    Note that \( t_\mathrm{d} \) also is used as the start time for planning patrol trajectories for the tugs to follow.

  2. 2.

    http://www.haskell.org.

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Acknowledgements

The SoftICE lab is grateful for the support provided by Regionalt Forskningsfond Midt-Norge and the Research Council of Norway through the project Dynamic Resource Allocation with Maritime Application (DRAMA), grant no. ES504913.

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Authors and Affiliations

  1. Software and Intelligent Control Engineering Laboratory, Faculty of Engineering and Natural Sciences, Aalesund University College, Postboks 1517, 6025, Åalesund, Norway

    Robin T. Bye & Hans Georg Schaathun

Authors
  1. Robin T. Bye
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  2. Hans Georg Schaathun
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Correspondence to Robin T. Bye .

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Editors and Affiliations

  1. EPFL SB-DO, Lausanne, Switzerland

    Dominique de Werra

  2. MAS of INFORMS, Madison, Alabama, USA

    Greg H. Parlier

  3. Complutense University, Madrid, Spain

    Begoña Vitoriano

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Bye, R.T., Schaathun, H.G. (2015). A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms. In: de Werra, D., Parlier, G., Vitoriano, B. (eds) Operations Research and Enterprise Systems. ICORES 2015. Communications in Computer and Information Science, vol 577. Springer, Cham. https://doi.org/10.1007/978-3-319-27680-9_11

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  • DOI: https://doi.org/10.1007/978-3-319-27680-9_11

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  • Publisher Name: Springer, Cham

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