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- W2393314882 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." @default.
- W2393314882 created "2016-06-24" @default.
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- W2393314882 date "2015-01-01" @default.
- W2393314882 modified "2023-09-29" @default.
- W2393314882 title "A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms" @default.
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- W2393314882 doi "https://doi.org/10.1007/978-3-319-27680-9_11" @default.
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