2001
DOI: 10.14214/sf.597
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Outranking methods as tools in strategic natural resources planning

Abstract: Two outranking methods, ELECTRE III and PROMETHEE II, commonly used as decision-aid in various environmental problems, and their applications to decision support for natural resources management are presented. These methods represent 'the European school' of multi-criteria decision making (MCDM), as opposed to 'the American school', represented by, for instance, the AHP method. On the basis of a case study, outranking methods are compared to so far more usually applied techniques based on the ideas of multi at… Show more

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Cited by 128 publications
(103 citation statements)
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“…This method can be considered as a non-compensatory one, i.e. an alternative low score under a criterion cannot be compensated by high scores on other criteria [27]. Another important feature of the method is consideration of incomparability.…”
Section: The Fuzzy Sets In the New Approachmentioning
confidence: 99%
“…This method can be considered as a non-compensatory one, i.e. an alternative low score under a criterion cannot be compensated by high scores on other criteria [27]. Another important feature of the method is consideration of incomparability.…”
Section: The Fuzzy Sets In the New Approachmentioning
confidence: 99%
“…Some studies present these variations as an observation and highlight the strongest ranking differences and similarities produced by the methods employed. Kangas et al (2001), for example, used Multi-Attribute Utility Theory (MAUT), ELimination Et Choix Traduisant la REalité (ELECTRE III), and PRO-METHEE II for planning strategic natural resources, while Opricovic and Tzeng (2007) used VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR), TOPSIS, ELECTRE, and PROMETHEE for evaluating hydropower systems. Other studies have gone an extra step in attempting to explain the variations through a sensitivity analysis by modifying the values of certain elements (e.g., criteria weights, maximum, and minimum thresholds) and observing the changes that occur to the ranking results.…”
Section: Parallel Applicationsmentioning
confidence: 99%
“…Kangas et al (2001) indicated that the number of criteria may be limited to nine in order to minimize the probability of rank reversal during simulation and to ease comprehension. Katukiza et al (2010) and Sadr et al (2013) employed five criteria in their studies.…”
Section: Justification Of the Evaluation Criteria Employedmentioning
confidence: 99%