{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:27:30Z","timestamp":1760243250249,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2014,5,26]],"date-time":"2014-05-26T00:00:00Z","timestamp":1401062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The objective of this paper is to devise a strategy for developing a flexible tool to efficiently install a marine energy farm in a suitable area. The current methodology is applied to marine tidal current, although it can be extended to other energy contexts with some adaptations. We introduce a three-step approach that searches for marine farm  sites and technological solutions. The methodology applied is based on a combination of Geographic Information Systems (GIS), multi-criteria analysis (MCA) and an optimization algorithm. The integration of GIS and MCA is at the core of the search process for the best-suited marine areas, taking into account geographical constraints, such as human activity, pressure on the environment and technological opportunities. The optimization step of the approach evaluates the most appropriate technologies and farm configurations in order to maximize the quantity of energy produced while minimizing the cost of the farm. Three main criteria are applied to finally characterize a location for a marine energy farm: the global cost of the project, the quantity of energy produced and social acceptance.  The social acceptance criterion is evaluated by the MCA method, Electre III, while the optimization of the energy cost is approximated by a genetic algorithm. The whole approach is illustrated by a case study applied to a maritime area in North-West France.<\/jats:p>","DOI":"10.3390\/ijgi3020781","type":"journal-article","created":{"date-parts":[[2014,5,27]],"date-time":"2014-05-27T02:36:58Z","timestamp":1401158218000},"page":"781-799","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Geographical-Based Multi-Criteria Approach for Marine Energy Farm Planning"],"prefix":"10.3390","volume":"3","author":[{"given":"Nicolas","family":"Maslov","sequence":"first","affiliation":[{"name":"Naval Academy Research Institute, 29240 Brest Cedex 9, France"}]},{"given":"David","family":"Brosset","sequence":"additional","affiliation":[{"name":"Naval Academy Research Institute, 29240 Brest Cedex 9, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5586-1997","authenticated-orcid":false,"given":"Christophe","family":"Claramunt","sequence":"additional","affiliation":[{"name":"Naval Academy Research Institute, 29240 Brest Cedex 9, France"}]},{"given":"Jean-Fr\u00e9d\u00e9ric","family":"Charpentier","sequence":"additional","affiliation":[{"name":"Naval Academy Research Institute, 29240 Brest Cedex 9, France"}]}],"member":"1968","published-online":{"date-parts":[[2014,5,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Multon, B. 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