Research On Dynamic Group Decision Making Theory And Application For Investment Projects Of The Large Central Enterprise Group

With the changing of the international environment and the market environment,the investment project decision of the large central enterprise group is facing more complex and multilateral external environment.The competition of enterprises is increasing,the complexity of decision-making is increasing,and the demand for scientific decision-making is increasing.The increasing competition of enterprises leads to the complexity of decision-making.The demand for scientific decision-making has also increased.Meanwhile,with the diversification of decision data,and the rapid development of big data,cloud platform and artificial intelligence,a new decision mode and decision technology supported by network information technology are formed.For the central enterprise group itself,with the continuous expansion of scale and business,and the increasing democratization of internal management,the decision-making process is often characterized by large scale of investment and high investment risk,and it involves the experts of large groups.Therefore,the advantages of group decision-making in central enterprise groups' investment projects are increasingly prominent.Although there are many research achievements in the theory of group decision-making,there is still a lot of research space in the fields of the expansion of the algorithm,the research of mixed multi-attribute system and the dynamic interactive research.Further research on the design and application of group decision-making system is still needed to be improved.Therefore,this paper takes the dynamic group decision-making of the investment project of the central enterprise group as the research object,and supported by the cooperative research on the investment decision-making platform of a petroleum enterprise.The research is carried out from two perspectives:group decision-making theory algorithm and group decision-making system.The innovative studies include:Firstly,several kinds of extended multi-attribute group decision-making methods based on interval triangular fuzzy numbers are proposed.Above all,the entropy and cross entropy of the interval triangular fuzzy number,the aggregation operator(the weighted arithmetic operator of the interval triangular fuzzy numbers ITF-WAA,the weighted geometric mean operator of the interval triangular fuzzy number ITF-WGA)are defined.Then,on the basis of the definition of the degree of possibility,several classes of ordered aggregation operators(Interval triangular fuzzy numbers ordered weighted arithmetic averaging operator ITF-OWA,Interval triangular fuzzy numbers ordered weighted geometric averaging operator ITF-OWGA and Prioritzed algorithm based on probability ranking)are proposed.The extended entropy weight-VIKOR multi attribute group decision-making method based on the interval triangular fuzzy number,the extended entropy weight-TOPSIS algorithm,and the interval triangular fuzzy multi-attribute group decision-making expansion algorithm based on the priority order are proposed.Finally,for the group decision-making of the investment project of the petroleum enterprise,the numerical case analysis and the sensitivity analysis are carried out,and the stability and adaptability of each algorithm proposed in this paper are verified and analyzed.To a certain extent,this research supplements and improves the deficiency of the multi-attribute group decision-making theory system based on interval triangular fuzzy numbers.Secondly,a hybrid dynamic multi-attribute decision-making method based on two-element connection number is proposed.In this method,the hybrid multi-attribute system which includes the exact number,the interval number,the interval triangular fuzzy number and the fuzzy semantic form is studied.The two-element connection number is used as the unified form of the mixed attribute system,and the determinacy and uncertainty in the decision information are synthetically measured,and the two-element connection number will be used as the form.The unified form of the mixed attribute system achieves better characterization of certainty and uncertainty in decision information.On this basis,the extended entropy weight-VIKOR multi-attribute group decision-making method based on the interval triangular fuzzy number,the extended entropy weight-TOPSIS algorithm,and the interval triangular fuzzy multi-attribute group decision-making expansion algorithm based on the priority order are proposed.Furthermore,the algorithm is verified with relevant examples,and compared with the traditional principal value decision principle and the comprehensive decision value principle algorithm.Finally,considering the dynamics of multi-attribute group decision-making in enterprise decision,a method of determining the weight of time entropy weight and entropy weight is proposed to support dynamic decision analysis.This research has formed a research framework for uncertain mixed multi-attribute decision-making and its dynamic analysis,which has been supplemented to the current research field of mixed multiple attributes.Thirdly,the research on the method of determining the weights of experts and the dynamic interactive evolution of expert opinion groups in large group decision-making are carried out.In view of the large group characteristics in the decision-making process of the central enterprise group,the intra group and inter group expert weight algorithms are defined on the basis of a large group clustering algorithm combined with the cohesive hierarchical clustering and K-means clustering.In addition,based on complex networks,an extended DEMATEL method of determining the weight is proposed,which considers the relationship between experts,the level and ability of expert's knowledge and the level of experts,and can be used to determine the core nodes of the decision system.Furthermore,the dynamic interactive evolution mechanism between experts and groups is analyzed,and an improved SInR algorithm is proposed to measure the dynamic interaction mechanism.MATLAB and web crawler technology are used to analyze the algorithm.This study provides an effective decision-making method for information gathering,opinion interaction and other issues in the situation of large groups of experts.Based on the above algorithm analysis,this paper proposes a dynamic group decision-making algorithm system for central enterprise group' s investment projects.And the application research is carried out according to the characteristics of central enterprise group decision-making.Fourthly,a group decision making index system for investment projects of petroleum enterprise is put forward.Through the research on the decision-making characteristics of large central enterprise group and the research focus of petroleum enterprises,this paper puts forward the decision index system of investment projects based on dimensions of strategic factors,economic factors,risk factors and environmental factors,which provide a certain reference for enterprise decision-making practice.Fifthly,an intelligent group decision system framework for central enterprise group's investment project is designed.According to the background of current big data intelligence decision,the characteristics of central enterprise group,and the analysis of group decision system,this paper constructs an intelligent group decision-making system for investment project of central enterprise group,and designs and analyses each module,then forms a comprehensive framework of intelligent group decision-making system to support the decision making of enterprise group.This paper,to a certain extent,supplements the research on interval triangular fuzzy multi-attribute group decision-making,two-element multiple-attribute group decision-making,mixed multi-attribute group decision-making and dynamic group decision-making,and proves the validity and stability of the algorithm combined with numerical case and empirical analysis.The research on group decision-making system of the central enterprise group's investment project under the background of big data provides guidance for the construction of the group decision-making platform of the central enterprise group.