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Multiple criteria decision making (MCDM) problems are studied mainly under two categories, namely multiple objective decision making (MODM) problems and multiple attribute decision making (MADM) problems.
Decisions on attribute weights are important problems in multiple attribute decision making.
In that regard, the UPL problem is converted into a Multiple Attribute Decision Making (MADM) problem.
The Multiple Attribute Decision Making (MADM) problem deals with candidate priority alternatives with respect to various attributes.
Lectotype optimization involves multiple objectives with uncertainty and so is a problem of multiple attribute decision making.
In classical multiple attribute decision making (MADM) methods, the ratings and the weights of the criteria are known precisely.
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This method is especially designed to evaluate alternatives in multi criteria or multi-attribute decision making.
This paper presents two interval type 2 fuzzy multi-attribute decision making methods for material selection.
It combines a knowledge acquisition technique, a multi-attribute decision making technique, a validation technique and a machine learning algorithm.
The method was developed by extending two known approaches: "fuzzy composite programming" and "multi-attribute decision making with dominance in the attributes".
This study presents a novel Multi-Attribute Decision Making (MADM) model for evaluating a range of potential mission scenarios for the human exploration of Mars.
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