1999
DOI: 10.1007/s001580050065
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A preference ordering among various Pareto optimal alternatives

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Cited by 41 publications
(59 citation statements)
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“…Most individuals find it difficult or impossible to intuitively choose a "best solution" from a set of several alternatives with more than three criteria because of one's limited ability to visualize or think in a greater than three-dimensional space [Das, 1999]. MAUA transforms the MCDA problem from the multi-dimensional space into a one-dimensional scalar function.…”
Section: A Suitable Level Of Detail For Trade Studiesmentioning
confidence: 99%
“…Most individuals find it difficult or impossible to intuitively choose a "best solution" from a set of several alternatives with more than three criteria because of one's limited ability to visualize or think in a greater than three-dimensional space [Das, 1999]. MAUA transforms the MCDA problem from the multi-dimensional space into a one-dimensional scalar function.…”
Section: A Suitable Level Of Detail For Trade Studiesmentioning
confidence: 99%
“…That is, if the benefits to choosing S (for the gainers) are large enough to create a surplus value that allows the compensation of those who prefer Q (who would, in effect, ''lose'' by moving from Q to S), unanimity can still be achieved. The gainers compensate the losers, and the result is a Pareto improvement, because (after the 7 For technical conditions on the ranking of Pareto optima, see Das (1999) and Keeney and Kirkwood (1975). 8 The presumption in favor of autonomy is part of the standard ''liberal'' precepts.…”
Section: Why the Pareto Criterion Is Appropriate As A Benchmarkmentioning
confidence: 99%
“…Besides, due to some subjective factors of decision makers, the aggregation approach cannot always guarantee that all final choices are strictly reasonable. However, in contrast, a Pareto domination approach, called successive elimination of alternatives based on order and degree of efficiency (SEABODE), does not need to specify weigh coefficients to any evaluation criterion and can overcome the drawbacks of aggregation approaches [34]. The SEABODE is based on two theorems: efficiency of order k and efficiency of order k with degree p. For a feasible set of a large number of design alternatives, the SEABODE to select the preferred alternatives involves two steps: (1) find all alternatives belonging to the same lowest order of efficiency, recorded as k min ; (2) among the result set, only retain the alternatives that are efficient of order (k min´1 ) with highest degree p max .…”
Section: The Seabode Approachmentioning
confidence: 99%