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A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms

Bye, Robin Trulssen; Schaathun, Hans Georg
Chapter
Published version
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2015-ByeSchaathun.pdf (Locked)
URI
http://hdl.handle.net/11250/2499053
Date
2015
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  • Institutt for IKT og realfag [258]
  • Publikasjoner fra CRIStin - NTNU [21000]
Original version
10.1007/978-3-319-27680-9_11
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.
Publisher
Springer Verlag

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