| Fuzzy multiple attribute deeision making (FMADM) theory is an important branch of moderndecision science. Compared with traditional multiple attribute deeision making (MADM) method,FMADM method can better deal with the fuzziness of human thinking, uncertainty andcomplexity of objective things, and it has been widely and successfully used by country, society,enterprises and people. So, carrying out the study on FMADM is of high value both in theory andpratice. Aiming at further improvement for FMADM theory, the main structure of this paper isdetailed as follows:1. Study on the distance and similarity measures between intuitionistic fuzzy sets (IFSs) orinterval-valued fuzzy sets (IVFSs). This paper puts forward a new kind of distance measure forIFSs and proves that the measure proposed satisfy the properties of axiomatic definition fordistance measure between IFSs. This method contains information of all points on the interval ofIVFSs and assumes that different points on the interval provide different amount of informationfor distance measure, i.e., the closer the point is from the midpoint, the more information it canprovide. As a result, this distance measure can overcome the drawback of information loss to alarge extent.2. Study on entropy measures for IFSs. Based on some widely used distance measures andintuitionistic index, this paper proposes a series of entropy measures for IFSs, which meet theaxiomatic requirements of entropy measure for IFSs. The entropies construced in this paper takeall three functions into account, i.e., intuitionistic index, degree of membership andnonmembership. The examples provided demonstrate that the results produced by entropiesaforementioned are consistent with people’s intuition.3. Study on MAMD under interval-valued intuitionistic fuzzy environment (IVIFE) withincomplete attribute weight information. This paper puts forward two methods to determine theattribute weights in MAMD underIVIFE with incomplete attribute weight information. In the firstmethod, theH p,qoperator, fuzzy linear programming and extended TOPSIS are integrated toderive the attribute weights. In the second method, a series of programming models based oncross-entropy are constructed and eventually aggregated into a single objective linearprogramming model, from which the attribute weights are obtained. Then, all the alternaives areranked based on extended TOPSIS and concept of likelihood.4. Study on multiattribute group decision making (MAGDM) method based on aggregationoperators with Interval-valued2-tuple linguistic information. This paper proposes theinterval-valued2-tuple linguistic model and introduces its score and accuracy functions forcomparison between interval-valued2-tuples. In addition, a series of aggregation operators ofinterval-valued2-tuples, together with their properties, are presented, such as interval-valued 2-tuple weighted average (IVTWA) operator, interval-valued2-tuple ordered weighted average(IVTOWA) operator, the interval-valued2-tuple weighted geometric (IVTWG) operator, theinterval-valued2-tuple ordered weighted geometric (IVTOWG) operator, the generalizedinterval-valued2-tuple weighted average (GIVTWA) operator and the generalized interval-valued2-tuple ordered weighted average (GIVTOWA). Furthermoer, based on the concept of degree ofprecision, a new method to determine the weight vector of interval-valued2-tuple aggregationoperator is put forward.5. The application of FMADM method in service innovation management–a case study ofinternet bank. On the basis of quality function development (QFD) and four-dimensional model ofservice innovation, this paper develops the customer oriented service innovation model and applysthis model to pratice in innovation management of internet bank, where the importance degree ofcustomer demands and innovation elements, and degree of closeness among them are derived byFMADM method. At last, countermeasures and suggestions are put forward for improvement ofinnovation performance in internet bank. |
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