The Method And Application Of Multiple Attribute Decision-Making

Multiple attribute decision-making, which is one of the most important parts of decision-making theory and modern decision-making science, is widely used in many fields, such as: engineering designs, society, economy, management, military affairs et.al. Now it plays a role in investment decision-making, intern evaluation, optimizing alternatives, selecting the address of factory, comprehensive evaluating on economic results, et al. It is an interesting thing to study more useful and effective multiple attribute decision-making approaches, especially in view of application .The main cotent and achievement of this thesis are the following:In Chapter 1, in view of some intrinsic characteristics in subjective and objective weighting methods, and on the basis of the optimization theory this paper propose a new integrated approach to determine attribute weights in multi-attribute decision making problems, the proposed method not only utilize objective information sufficiently but also reflect the preference of decision-maker, which makes the determined attribute weights more reasonable and feasible.In Chapter 2, With some indices embodying the general characteristics of the fuzzy numbers, the expectations of the fuzzy numbers, the middle points and the spreads of a-cut sets, this paper proposes a new approach to rank the fuzzy numbers by the following method: first, translate parallel the expectations of the fuzzy numbers to the original point; second, make a convex combination of the middle point and the spread of each en-cut set; then, weight average the convex combinations on all a-cut sets and the weighted consequence and the expectations of the fuzzy numbers, finally the proposed comparison function is the outcome. It is unnecessary for our proposed ranking approach to make all pairwise comparisons, thus simplifying computation and acquiring an absolute order relation at the same time, according to the comparison function on the basis of real set.In Chapter 3, Popularizing L-R fuzzy numbers in Chapter 2 to general fuzzy numbers,the thesis defines the mean of fuzzy number under the basis of uniform distribution and proportional dittribution, takes advantages of the middle point and spread, proposes a new fuzzy ranking approach through a method of weighted mean.In Chapter 4, This thesis combines the utility index of Chen with integrally characteristic, and the utility index of expectation and standard deviation with partially characteristic, making use of their advantages, proposes a new ranking function with multiple indices, which embodies both the partial and global characteristics of the fuzzy number. Also this new method is compared with other methods by through numerical examples.In Chapter 5, Reciprocal judgement matrix is a kind of fuzzy preference information form given by decisions makers through pairwise comparison on indices. This paper proposes a new approach ranking fuzzy numbers according to the reciprocal judgement matrix with trapezium fuzzy numbers.