Research On Methods Of Hybrid Multiple Attribute Group Decision Making

In recent years, the uncertain multi-attribute decision-makings have arousedacademic circle's widespread interest, and interval multi-attribute decision-making isone of them. Because the complex decision-making environment, the limit of humancognition, the decision-maker frequently cannot or difficult to produce a crisp numberof the decision information, but easy to produce the decision information in the formof interval numbers or language. The uncertain decision information is more scientificand reasonable, and lightens the burden of the decision-maker.With the development of society and science & technology, people need morestrongly for the scientifcalness and democratization of decision. In reality, importantdecisions are often not just made by one person, but made together by manydecision-makers (decision expert group). Moreover, in real world of nowadays,problems faced by people become greater, more and more complicated, and gobeyond individual decisive capability by far. During the process of importantdecisions, to avoid decisive faults, the establishment of decisive projects often needthe coordination and cooperation of a decisive group in an organization, and theresearch on the group decision-making theory need speed up to adopt to the urgentneed of the situation.For the two hotspots in the decision-making theory, the hybrid multiple attributegroup decision making is studied from the two aspects study.1. For the hybrid multiple attribute Decision making problem with incompleteinformation on attribute weights to which the attribute values are given in terms ofreal number, interval number and natural language, a new Grey Relational Analysis(GRA) method is proposed, which is the extension of the traditional GRA algorithm.In the method, the grey relational degree for hybrid index sequences is introduced todetermine the relation degree between every alternative and the positive ideal point.Then, the part optimization models and the global optimization model are constructedto seek incomplete attribute weights, on the basis of which grey appraisal value ofevery alternative corresponding to the ideal solution is calculated to rank allalternatives. At last, a numerical example is provided to illustrate the proposedmethod. The result shows the approach is simple, effective and easy to calculate.2. For the hybrid multiple attribute group decision making problems to whichthe attribute values are given in terms of real number, interval number and natural language, in the paper, firstly the fuzzy language is transform it into a two-duplelinguistic symbol, then three operators of aggregating information are to aggregatethree types of uncertain decision information given by each decision maker. Threeoperators of aggregating information are hybrid weighted averaging operator, hybridcontinuous interval argument weighted averaging operator and two-duple linguisticsymbol operator. The operators solve weights of the dates own and the location of thedates at the same time. All individual preference information is aggregated intocollective preference P=[P_ij] and P_ij is real number which is easy to calculate.The alternatives are ranked from the opinion matrix P=[p_ij] of group by greyrelational analysis. At last, the approach is showed simple, effective too by illustratingexample.