{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T00:25:04Z","timestamp":1762043104424,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643682242"},{"type":"electronic","value":"9781643682259"}],"license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,29]]},"abstract":"<jats:p>This article aims to present with more details, the multicriteria decision aid SAPEVO-M-NC (Simple Aggregation of Preferences Expressed by Ordinal Vectors - Non-Compensatory - Multi Decision Makers). It is a new version of the SAPEVO-M method, of an ordinal, non-compensatory nature and with the possibility of acting by multiple decision makers. As a result, the method provides information on the partial weights, indicating the relative importance of the criteria for each of the decision makers, the relative dominance values and two evaluations on the performance of the alternatives: a partial one, which considers the absolute dominance indices, being used to assess existing dominance relationships; and a global one, which provides the performance rates of the alternatives, making it possible to order them as well as to carry out a sensitivity analysis on the observed performances, reflecting in greater transparency in the decision-making process.<\/jats:p>","DOI":"10.3233\/faia210235","type":"book-chapter","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T17:31:29Z","timestamp":1635874289000},"source":"Crossref","is-referenced-by-count":7,"title":["The SAPEVO-M-NC Method"],"prefix":"10.3233","author":[{"given":"S\u00e9rgio Mitihiro do Nascimento","family":"Ma\u00eada","sequence":"first","affiliation":[{"name":"Federal Fluminense University, Brazil"},{"name":"Naval Systems Analysis Center, Brazil"}]},{"given":"Marcio Pereira","family":"Bas\u00edlio","sequence":"additional","affiliation":[{"name":"Military Police of the State of Rio de Janeiro, Brazil"}]},{"given":"Igor Pinheiro de Ara\u00fajo","family":"Costa","sequence":"additional","affiliation":[{"name":"Federal Fluminense University, Brazil"},{"name":"Naval Systems Analysis Center, Brazil"}]},{"given":"Miguel \u00c2ngelo Lellis","family":"Moreira","sequence":"additional","affiliation":[{"name":"Federal Fluminense University, Brazil"},{"name":"Naval Systems Analysis Center, Brazil"}]},{"given":"Marcos","family":"dos Santos","sequence":"additional","affiliation":[{"name":"Military Institute of Engineering, Brazil"},{"name":"Naval Systems Analysis Center, Brazil"}]},{"given":"Carlos Francisco Sim\u00f5es","family":"Gomes","sequence":"additional","affiliation":[{"name":"Naval Systems Analysis Center, Brazil"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Modern Management based on Big Data II and Machine Learning and Intelligent Systems III"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA210235","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T17:31:32Z","timestamp":1635874292000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA210235"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,29]]},"ISBN":["9781643682242","9781643682259"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia210235","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"type":"print","value":"0922-6389"},{"type":"electronic","value":"1879-8314"}],"subject":[],"published":{"date-parts":[[2021,10,29]]}}}