4.7 Article

Multiple attribute decision making considering aspiration-levels: A method based on prospect theory

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 65, Issue 2, Pages 341-350

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2013.02.013

Keywords

Multiple attribute decision making (MADM); Aspiration-level; Prospect theory; Gain; Loss; Ranking

Funding

  1. National Science Fund for Excellent Innovation Research Group of China [71021061]
  2. National Science Foundation of China [71271051, 71001020, 71071029]
  3. Fundamental Research Funds for the Central Universities, NEU, China [N110706001]

Ask authors/readers for more resources

In this paper, a method based on prospect theory is proposed to solve the multiple attribute decision making (MADM) problem considering aspiration-levels of attributes, where attribute values and aspiration-levels are represented in two different formats: crisp numbers and interval numbers. According to the idea of prospect theory, aspiration-levels are firstly regarded as the reference points, and the four possible types for comparing an attribute value with an aspiration-level are described. Then, for all possible cases of the four types, the calculation formulae of gains and losses of alternatives concerning attributes are given. By calculating gain and loss of each alternative, a gain matrix and a loss matrix are constructed, respectively. Further, using the value function proposed in prospect theory and the simple additive weighting method, the overall prospect value of each alternative is calculated. Based on the obtained overall prospect values, a ranking of alternatives can be determined. Finally, a numerical example is used to illustrate the use of the proposed method. (C) 2013 Elsevier Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available