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Comparison of multicriteria analysis techniques for decision making on floating offshore wind farms site selection

Díaz, H, Loughney, S, Wang, J and Guedes Soares, C (2022) Comparison of multicriteria analysis techniques for decision making on floating offshore wind farms site selection. Ocean Engineering, 248. ISSN 0029-8018

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This work compares two methodologies to assess different selection approaches, the Analytic Hierarchy Process (AHP) and Multiple Attribute Decision Analysis (MADA) using a combined Evidential Reasoning (ER) and AHP approach. This evaluation is done depending on: the number of alternative criteria, agility through the process of decision-making, computational complexity, adequacy in supporting a group decision, and consistency of results. Case studies are presented to analyze the robustness of the methodology evaluation. The criteria used to evaluate and identify the best locations are adapted for each methodology to proceed with the comparison. The results show that each approach is suitable for the problems of wind farm location selection, particularly toward the support of group decision-making and uncertainty modelling. The sites are ranked based on their respective weights for AHP and MADA. In terms of computational complexity, the complete AHP method performs better than the combined MADA and AHP approaches. Nevertheless, the MADA method is less time-consuming and convenient for selecting floating farm locations due to the smaller involvement of experts and corresponding higher agility during decision-making. Both methodologies demonstrate several alternative processes and criteria, adequacy in supporting a group decision, and adaptation in terms of criteria insertion or removal.

Item Type: Article
Uncontrolled Keywords: 0405 Oceanography, 0905 Civil Engineering, 0911 Maritime Engineering
Subjects: G Geography. Anthropology. Recreation > GC Oceanography
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TC Hydraulic engineering. Ocean engineering
Divisions: Engineering
Publisher: Elsevier
Date Deposited: 08 Apr 2022 08:59
Last Modified: 26 Feb 2023 00:50
DOI or ID number: 10.1016/j.oceaneng.2022.110751
URI: https://researchonline.ljmu.ac.uk/id/eprint/16626
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