Research On Decision-making Methods And Applications Based On Weakened Hedged Probabilistic Linguistic Information

A decision-making problem contains three parts: make a decision-making problem,ensure objectives,and select an optimal alternative.The efficient decision-making expression is necessary to ensure the efficiency of decision-making results.It is significant how to display and apply information to decision-making problems.In the decision-making process,so as to dismiss the complexity of decision-making information,the uncertainty of outside,and the characters of experts,decision-makers believe that linguistic variables are an effective way to express uncertain information.Complex linguistic expressions can effectively depict qualitative and quantitative information,such as weakened hedged probabilistic linguistic term sets.This paper analyzes the weakened hedged probabilistic linguistic information through the decisionmaking theory.And the details are listed as follows:(1)At the theoretical level,firstly,a weakened hedged probabilistic linguistic term set is defined based on linguistic terms with weakened hedge sets and probabilistic linguistic term sets.The weakened hedged probabilistic linguistic term set evaluates weakened hedges from linguistic hedges and probability theory.The weakened hedged probabilistic linguistic term set,therefore,represents information from hedges and hedge degrees,which combines quantity and quality expressions.Besides,some related operational rules and comparison rules are defined.Secondly,a probabilistic improvement model of the weakened hedged probabilistic linguistic term set is constructed in terms of the evidence reasoning theory.The probabilistic improvement model transforms the weakened hedged probabilistic linguistic term set into one or more probabilistic linguistic term sets,which can effectively calculate the decision information,which units various hedged degrees and calculate information effectively.Preference relation is an important part of the decision-making support model,the theory of individual weak consistency,additive consistency,and satisfy consistency based on weakened hedged probabilistic linguistic preference information is studied.After meeting individual consistency,this paper studies the group consensus of the weakened hedged probabilistic linguistic term set.Based on defining the related concepts of weakened hedged probabilistic linguistic term sets,this paper studies expressions and decision-making methods based on the weakened hedged probabilistic linguistic term information and expands the development of decision-making theory.(2)At the method level,the bi-projection method,the dual weighted discount method,and algorithms of individual consistency and group consensus are studied in terms of the weakened hedged probabilistic linguistic information.According to the grey theory and the characteristics of the weakened hedged probabilistic linguistic term set,the bi-projection takes the linguistic term set and the weakened hedge set of the weakened hedged probabilistic linguistic term set as the ”white part” and ”grey part”.Using the grey theory,the bi-projection method analyzes decision-making information from the perspectives of positive ideal solutions,negative ideal solutions and alternatives,which display information from multi-side points.The dual weighted discount method express information with the belief function and plausibility function.Evidence reasoning theory and discount method are used to classify,integrate information,and rank alternatives.This paper analyzes the improved algorithms of the weak consistency and satisfactory consistency considering the weakened hedged probabilistic linguistic preference information.At the same time,the consensus-reaching algorithms are established based on the weakened hedged probabilistic linguistic preference information.Compared to the previous group consensus judgment,the paper proposes a random threshold algorithm using hedged linguistic preference information,which reduces the influence of threshold setting on group consensus results and thus creates an objective,dynamic,and effective group.(3)At the application level,the weakened hedged probabilistic linguistic term set is applied to the risk management process of the PPP subway project.This paper establishes a biprojection model based on the weakened hedged probabilistic linguistic term information and applies it to the failure mode impact analysis process in terms of the project life cycle.Then,this paper analyzes the private selecting process in terms of the probabilistic improvement model.Besides,preference relation as a method to express information directly,this paper analysis individual weak consistency and satisfies consistency with the risk evaluation process.Group consensus as a part of the decision-making support model,this paper established an evaluation process of government subsidy programs.The failure mode impact analysis of PPP subway projects provides experience for risk management,the private sector selection for PPP subway projects promotes implementation,the risk assessment of PPP subway projects lays the groundwork for risk allocation mechanisms construction,and the selection of government subsidy schemes ensures smooth operations during the construction phase.In total,this paper studies methods of the weakened hedged probabilistic linguistic term set,and applies them to the process of failure model impact analysis,the selecting of private partners,the risk evaluation process,and the selection of government subsidy schemes,which display the efficiency of the weakened hedged probabilistic linguistic term set.This paper improves decision-making theory and provides theoretical methods for solving decision-making problems.Therefore,this paper enriches decision-making in theory and application,which not only has theoretical significance but also has certain practical application value.