Journal
COMPUTERS & INDUSTRIAL ENGINEERING
Volume 87, Issue -, Pages 150-162Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2015.04.016
Keywords
Decision analysis; Evidential reasoning approach; Determination of attribute weights; Deviation incompatibility among attributes; Decision incompatibility among attributes
Funding
- Research Grants Council of the Hong Kong Special Administrative Region, China [CityU112111]
- National Natural Science Foundation of China [71131002, 71201043, 70925004, 71231007]
- National Key Basic Research Program of China [2013CB329603]
- Humanities and Social Science Foundation of the Ministry of Education in China [12YJC630046]
- Natural Science Foundation of Anhui Province of China [1408085MG136]
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Decisions on attribute weights are important problems in multiple attribute decision making. Many methods have been proposed to create attribute weights which are used to aggregate attributes in a simple additive weighting way. In this paper, a method of deriving attribute weights from incompatibility among attributes and possible constraints on the weights is developed based on the evidential reasoning approach in which attribute aggregation is nonlinear rather than linear. The incompatibility is a flexible combination of deviation incompatibility and decision incompatibility with a relaxation coefficient. The deviation incompatibility measures differences between assessments of alternatives on each attribute and the decision incompatibility quantifies differences between assessments of alternatives on one attribute and the aggregated assessments of the alternatives. For a specific alternative, two pairs of optimization problems with a constraint on the difference between potential weights and the combination of deviation incompatibility and decision incompatibility are designed to generate the favorable intervals of attribute weights and those of utilities of assessment grades. A problem of car performance assessment is investigated to demonstrate the applicability of the proposed method. The method is validated by comparison with other methods of producing attribute weights using the problem. (C) 2015 Elsevier Ltd. All rights reserved.
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