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Authors: Robin T. Bye and Hans Georg Schaathun

Affiliation: Aalesund University College, Norway

ISBN: 978-989-758-075-8

Keyword(s): Receding Horizon Control, Genetic Algorithm, Dynamic Optimisation, Algorithm Evaluation, Modelling, Computational Simulation.

Related Ontology Subjects/Areas/Topics: Agents ; Applications ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Decision Support Systems ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mathematical Modeling ; Methodologies and Technologies ; Operational Research ; Optimization ; Resource Allocation ; Routing ; Simulation ; Symbolic Systems

Abstract: 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 RHGA can be configured. The set of these RHGA configurations are effectively equivalent to a set of different TFO algorithms that each can be used for dynamic tug fleet positioning. In order to compare the merit of TFO algorithms that solve the TFO problem as defined here, we propose two evaluation heuristics and test them by means of a computational simulation study. Finally, we discuss our results and directions forward.

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Paper citation in several formats:
T. Bye, R. and Georg Schaathun, H. (2015). Evaluation Heuristics for Tug Fleet Optimisation Algorithms - A Computational Simulation Study of a Receding Horizon Genetic Algorithm.In Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-075-8, pages 270-282. DOI: 10.5220/0005217802700282

@conference{icores15,
author={Robin T. Bye. and Hans Georg Schaathun.},
title={Evaluation Heuristics for Tug Fleet Optimisation Algorithms - A Computational Simulation Study of a Receding Horizon Genetic Algorithm},
booktitle={Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2015},
pages={270-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005217802700282},
isbn={978-989-758-075-8},
}

TY - CONF

JO - Proceedings of the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Evaluation Heuristics for Tug Fleet Optimisation Algorithms - A Computational Simulation Study of a Receding Horizon Genetic Algorithm
SN - 978-989-758-075-8
AU - T. Bye, R.
AU - Georg Schaathun, H.
PY - 2015
SP - 270
EP - 282
DO - 10.5220/0005217802700282

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