International Conference on Operations Research and Enterprise Systems

Operations Research and Enterprise Systems pp 165-190 | Cite as

A Simulation Study of Evaluation Heuristics for Tug Fleet Optimisation Algorithms

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 577)


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.


Receding horizon control Genetic algorithm Computational simulation Dynamic optimisation Algorithm evaluation Modelling Risk mitigation 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Software and Intelligent Control Engineering Laboratory, Faculty of Engineering and Natural SciencesAalesund University CollegeÅalesundNorway

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