A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms
نویسندگان
چکیده
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 tug fleet optimisation problem and present the details of 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 parallelisation and a 2D nonlinear mixed integer programming formulation of the problem.
منابع مشابه
Evaluation Heuristics for Tug Fleet Optimisation Algorithms - A Computational Simulation Study of a Receding Horizon Genetic Algorithm
A fleet of tugs along the northern Norwegian coast must be dynamically positioned to minimise the risk of oil tanker drifting accidents. We have previously presented a receding horizon genetic algorithm (RHGA) for solving this tug fleet optimisation (TFO) problem. Here, we first present an overview of the TFO problem, the basics of the RHGA, and a set of potential cost functions with which the ...
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