Title :
Method for hybrid multiple attribute decision making based on the maximum deviation
Author :
Nian, Zhang ; Lian, Yan ; Hao-Cheng, Wang ; Gui-wu, Wei ; Yan, Xiao
Author_Institution :
Dept. of Econ. & Manage., Chongqing Univ. of Arts & Sci., Chongqing
Abstract :
With respect to the problem of hybrid multiple attribute decision-making with incomplete information on attribute weights to which the attribute values are given in terms of precision number, interval number and fuzzy numbers, a new method is proposed. Firstly, the three different forms of numbers are unified into the form of interval number. The operational laws of interval numbers and a formula of possibility degree for the comparison between interval numbers, and then define the concept of deviation degree between interval numbers are introduced. An optimization model based on the maximizing deviation method, by which the attribute weights can be determined is established. The uncertain weighting average (UWA) operator is utilized to aggregate the interval numbers decosion making information corresponding to each alternative, and the formula of possibility degree is utilized to construct a possibility degree matrix (or called complementary judgement matrix), and then the priority formula of complementary judgement matrix is utilized to rank the alternatives and select the most desirable one(s). Finally, a numerical example is provided to illustrate the proposed method. The result shows the approach is simple, effective and easy to calculate.
Keywords :
decision making; fuzzy set theory; operations research; optimisation; possibility theory; attribute weight; complementary judgement matrix; fuzzy number; hybrid multiple attribute decision making; incomplete information; interval number; maximizing deviation method; maximum deviation; optimization model; possibility degree matrix; precision number; uncertain weighting average operator; Aggregates; Art; Decision making; Optimization methods; Deviation degree; Hybrid multiple attribute decision-making; Incomplete weight information; Interval numbers; Possibility degree;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597675