Research On Consistency And Consensus Of Large-Group Emergency Decision Making Based On Probabilistic Linguistic Preference Relation

In recent years,various serious and severe public crises and disasters have frequently occurred in China,posing a great threat to people’s lives and property.Considering the urgency of time and the complexity of emergencies,emergency command centers often organize experts in a large number of relevant departments to make decisions.This type of decision making is often called a large-group emergency decision making.After a severe disaster occurs,it is necessary to form a scientific and effective response plan in a short time and under high pressure.In this case,it is difficult for decision makers to use precise numerical values to express their preferences.Probabilistic linguistic preference relation based on probabilistic linguistic term set is a new tool for describing uncertain linguistic information,which conforms to the uncertainty of decision makers’ thinking in emergency decision making,and more accurately reflects the decision maker’s preference.The decision makers in large-group emergency decision making come from many different fields and represent different interests,which leads to widespread conflicts in decision making and it is difficult to effectively reach consensus.At the same time,due to the complex decision-making environment,the consistency of decision makers’ preferences based on pairwise comparisons of plans is difficult to guarantee.Therefore,it is necessary to construct a decision method for comprehensive consistency modification and consensus modification to meet the decision requirements in this case.Based on the research on existing decision making problems with probabilistic linguistic preference relation and the characteristics of large-group emergency decision making,this paper proposes a consistency modification algorithm and consensus modification algorithm based on probabilistic linguistic preference relation.The two algorithms are integrated and applied to the large-group emergency decision making problem,which effectively solves the problem of unacceptable decision maker consistency and low group consensus in the emergency decision making problem.The main research work of the paper is as follows:(1)The concept of dynamic modification parameters is proposed,and the linguistic values and probability values of probabilistic linguistic terms are modified using dynamic modification parameters.According to the current preference information and the modification target,each modification constructs a goal planning problem for the modified parameters,and solves the goal planning to obtain the current optimal modified parameters.The modification parameter changes with changes in preference information and modification goals.(2)Measure the cost of modification with the distance before and after the modification of the preference matrix.A time-constrained consistency modification algorithm is proposed.The algorithm builds the minimum cost consistency modification model so that the consistency is modified while the decision maker has the minimum modification cost.Time-constrained algorithm for large group consensus modification is proposed.A clustering algorithm based on probabilistic linguistic preference aggregates a large group into several subgroups.The subgroup preferences are aggregated to obtain the total group preference,and the subgroup farthest from the total group is used as the modified object.The algorithm builds the minimum cost consensus modification model so that the consensus is modified while the modified subgroup has the minimum modification cost.(3)Aiming at the problem that the consistency of decision makers is ignored in the existing research on group consensus,it is proposed that the consistency of decision makers should be checked and modified before consensus is reached.Integrate the consistency modification algorithm with consensus modification algorithm in largegroup emergency decision making.First,the consistency of decision makers is checked and modified.After the consistency of all decision makers is acceptable,the group consensus degree is measured and modified.After the consensus is reached,the schemes are ranked by the score function and the deviation function to select the optimal scheme.The comprehensive algorithm was applied to the simulation rescue of Tianjin chemical plant explosion,which verified the feasibility and effectiveness of the algorithm.