Research On Multiple Criteria Group Decision Making Based On Probabilistic Linguistic Term Sets

With the development of economy and the progress of science,decision-making is becoming more and more complex.From the decision makers' point of view,it is necessary to consider the decision-makers' personal experience,preferences and hesitation in the evaluation process,and to accurately express the evaluation information given by the decision-makers by using effective information expression method.From the decision-making method point of view,it is necessary to consider subjective and objective evaluation information,and to adopt corresponding decision-making methods to improve the efficiency of different decision-making problems.From the decision-making problems point of view,it is necessary to consider the complexity and development of different decision-making problems,and to adopt decision-making methods with high applicability to deal with complex decision-making problems.The accuracy of evaluation information given by decision makers,the efficiency and applicability of decision-making methods will affect the decision-making results.The multi-attribute group decision-making method needs to be improved with the problems of the new era.In this paper,the probabilistic linguistic term set and its processing method were researched,the attribute weight determination and the method of multi-attribute group decision-making with probabilistic linguistic term set were proposed to deal with complex problems.The experts evaluated with probabilistic linguistic term set.The probabilistic linguistic term set type evaluation information was transformed into order weighted hesitant fuzzy element type evaluation information in order to avoid the loss of information in the process of processing.Considering the advantages of subjective and objective weight determination methods.The weights of attributes were determined by combined weight determination method based on maximize the deviations.The classical decision-making problem was extended in the time dimension,and the probabilistic semantics multi-attribute group decision-making method was divided into single-stage probabilistic semantics multi-attribute group decision-making method and multi-stage probabilistic semantics multi-attribute group decision-making method.From the decision-makers' point of view,considering that the decision makers can't reach agreement on the selection of evaluation objects,the multi-stage probabilistic semantics multi-attribute group decision-making was divided into static and dynamic.In static multi-stage probabilistic semantics multi-attribute group decision-making,the experts have the same evaluation schemes.In dynamic multi-stage probabilistic semantics multi-attribute group decision-making,the experts select the scheme subset from the schemes to evaluate.To evaluate with probabilistic linguistic term set not only expresses the hesitation of decision makers in choosing semantic terminology,but also expresses decision makers' preference for semantic terminology.Using the order weighted hesitant fuzzy element to process the evaluation information ensures the accuracy of the evaluation information in the calculation process.To dividing the problem into single-stage and multi-stage,the development and multi-stage of the decision-making problems are considered.To dividing the multi-stage decision-making method into static and dynamic to improve the applicability of multi-attribute group decision-making method.Which satisfies the actual decision-making needs that decision makers have inconsistent selection of evaluation objects.Probabilistic linguistic term set was combined with decision theory in this paper,which not only enriches the existing theory and methods of multi-attribute group decision making,but also provides an accurate,efficient and applicable decision-making tool for practical complex decision-making problems.The effectiveness of the proposed method was verified by practical decision-making problems.