Research On The Method Of Collaborative Optimization About The Complex Group Decision-making System

With the size of group decision-making growing and the complexity of decision-making increasing, studying group decision-making problem has become a critical issue in the research field of group decision-making. However, there have been no systemic theory guidelines estabilished in the research field as a whole and few achievements have been made. Thus the exploring in this field is on its initial stage. Analysis and research in the field of complex group decision-making problem and its optimization mechanism are conducted in this thesis based on the theory and methods of complex science. The major work and innovative ideas are as follows:Firstly, the complexity of group decision-making system is systematically analyzed applying the theory of complex science and integrating the characteristic and nature of emergence. The emergence phenomenon and its definition of the complex group decision-making system were presented, and further research in the origin of emergence and its developing mechanism of the complex group decision-making system is conducted.Secondly, collaboration-guided theory, collaboration-dominated logic and the collaboration styles of the complex group decision-making system are presented herein based on the content and mechanism of emergence; and the collaborative frame of the multi-agent group decision-making support system is designed grounded on emergence.Thirdly, typical features of a kind of complex group decision-making issues with multi-layer structure are practically analyzed, and the standard forms and types of the leader-follower collaborative optimization model of the complex group decision-making system are built integrating the ideology of leader-follower optimization and the practical group decision-making issues with multilayer-structured organization.Fourthly, as to the difficult solution of the leader-follower collaborative optimization model of the complex group decision-making system, the collaborative-differential evolution algorithm is established based on differential evolution algorithm and species group density, referring to the theory and idea of collaborative evolution of the nature.Fifthly, the definition of the multi-disciplined complicated group decision-making problem of the large group with linguistic variance is presented, and a multi-disciplined collaborative optimization method upon the large group with linguistic variance is subsequently constructed, which is to measure the distance between the value of each individual plan discipline set and that of the group discipline ideal solution.Sixthly, as the decision-making group exhibited preference to information patterns in the plan appraisal, the thesis builds a satisfaction function of the decision-making group and sequentially a multi-patterned information collaborative optimization with maximum group satisfaction.