Abstract
Multiattribute decision-making is an important part of decision-making theory and modern scientific decision-making. It is widely used in engineering design, economic management, and so on. It is an important part of modern decision science to sort decision objects when considering multiple attributes. Due to time pressure and lack of understanding of decision-making problems, it is difficult for decision makers to accurately express judgment information. Decision-makers’ judgment information is more suitable to be expressed by intuitionistic fuzzy sets rather than deterministic numbers or linguistic variables. In the multiattribute decision-making problem, the size of attribute weight reflects the relative importance of each attribute. The research on attribute weight determination method is one of the core problems of multiattribute decision-making. Whether it is the subjective weighting method, the objective weighting method, or the combined weighting method, the research mainly focuses on deterministic multiattribute decision-making, mostly transforming fuzzy information into deterministic information for decision-making, which will lose a lot of information. Due to the differences of objective information data, a combined weighting method in different cases was proposed in this study. The original weight information and the prior information of standardized evaluation can be fully utilized in this model. The results indicate that when decision makers have preferences for different weighting methods, the combined weighting method can be determined according to the preference information of decision makers.
Highlights
Many problems faced by decision makers and incomplete fuzzy multiobjective decision-making problems because the characteristics of these problems often need the information of this kind of information [3–5]
When the decision maker has a preference for different weighting methods, it can be determined according to the decision-maker’s preference information
Aiming at the multiattribute decision-making problem in which the attribute weight is completely unknown or the weight information is partially determined, a combined weighting method based on variance maximization and information entropy is proposed in this study. ese two methods avoid the difficulty of obtaining preference information and make full use of the prior information of standardized evaluation
Summary
Multiattribute decision analysis has been widely used. e role of multiattribute decision-making in different application fields has been significantly enhanced. Attribute weight plays an important role in determining multiattribute decision-making. There are many engineering multiattribute decision-making problems, such as structural scheme optimization and design scheme evaluation Such problems generally require decision makers to provide preference information (attribute weight). En, Xu gives a decision-making method for the multiattribute decision-making problem in which the expert judgment information is intuitionistic fuzzy set and the attribute weight is partially unknown [23]. Li et al proposed a decision-making method based on fractional programming for the multiattribute group decision-making problem in which the expert judgment information and expert weight are intuitionistic fuzzy sets [24]. E research on the attribute weight determination method is one of the core problems of multiattribute decision-making [25, 26]. Compare the sensitivity of multiple schemes or decision objects, so as to select insensitive investment schemes when the economic benefit values are similar [42]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
