Irawan, Chandra Ade, Salhi, Said, Chan, Hing Kai (2022) A continuous location and maintenance routing problem for offshore wind farms: Mathematical models and hybrid methods. Computers & Operations Research, 144 . ISSN 0305-0548. (doi:10.1016/j.cor.2022.105825) (KAR id:94748)
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Official URL: https://doi.org/10.1016/j.cor.2022.105825 |
Abstract
In this study, we examine a challenging green logistical problem encountered with offshore wind farms: the integrated continuous location and maintenance routing problem wherein a service operation vessel and a safe transfer boat are used to maintain offshore turbines. Our aim is to dynamically and simultaneously determine the best locations for the service operation vessel in the plane (i.e. the sea) and the best delivery and pick-up routes by which the safe transfer boat can access the turbines. An optimisation model of the problem is first developed based on mixed-integer nonlinear programming to minimise the total maintenance cost. Given the limitations of this method, a novel algorithm that integrates a genetic algorithm, variable neighbourhood search, and a Weiszfeld-based algorithm is presented. To assess the performance of the proposed technique, a guided multi-start approach and a hybrid technique based on particle swarm optimisation are introduced. Moreover, our proposed method is shown to be easily adaptable to produce results that compete with those of state-of-the-art methods when it comes to solving a related continuous location routing problem. The computational results demonstrate the effectiveness and robustness of the proposed hybrid method.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.cor.2022.105825 |
Uncontrolled keywords: | Combinatorial optimisation, continuous location, location routing, hybridisation search, offshore wind farm |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Said Salhi |
Date Deposited: | 25 Apr 2022 14:56 UTC |
Last Modified: | 09 Oct 2023 23:00 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/94748 (The current URI for this page, for reference purposes) |
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