A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms
Chapter
Published version
Permanent lenke
http://hdl.handle.net/11250/2499053Utgivelsesdato
2015Metadata
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- Institutt for IKT og realfag [553]
- Publikasjoner fra CRIStin - NTNU [36890]
Originalversjon
10.1007/978-3-319-27680-9_11Sammendrag
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.