Combination Rules For Uncertain Information And Approaches To Decision Factors Under Group Decision Making Environment

Multiple attribute group decision making, as an important component of modern decision science, has long been the forefront in the decision analysis filed, and uncertain information is one of its basic features in practice. Therefore, how to effectively combine uncertain information and acquire decision factors (including attribute values and weight information) under group decision making environment becomes an interesting and important research topic with theoretical and practical significance.To improve the efficiency and quality of group decision making under uncertainty, this dissertation, with an idea of "decision factors acquisition→decision information combination→results comparative analysis→general method extraction", employs some theories and methods related to uncertain information processing as well as management decision analysis to make an in-depth study on combination rules for uncertain information and approaches to decision factors under group decision making environment, aiming to further enrich and improve the theories and methods for multiple attribute decision making under uncertainty, and to greatly enhance the practicality and flexibility of complex group decision making algorithms. Specifically, the main contents of this dissertation include:(1) Study on combination rules for uncertain information and on the decision model based on least point's principle under group decision making environment. For effective fusion of individual opinions of multiple decision makers, two different combination rules of evidence based on different strategy are presented, respectively. The two methods more effectively make use of global information such as the reliability, expected support, and the degree of cross merging between bodies of evidence, so as to determine the more satisfactory allocation strategy of evidential conflict, and therefore it has good adaptability to consistent or conflicting evidences, characterized by faster convergence rate and higher reliability. In order to obtain a wise decision result from aggregated opinions, the dissertation has an in-depth investigation on the decision model based on least point's principle, and successfully solves several key theoretical issues remaining in the model, making the model a practical decision making method with further perfection in theory.(2) Study on approaches to the weight information under group decision making environment. In view of the difficulty in determining decision makers'weights and attribute weights, a series of methods for group decision making under uncertainty have been proposed in such situation where attribute values are respectively expressed as exact values, intervals, intuitionistic fuzzy values (IFVs) and interval-valued intuitionistic fuzzy values (IVIFVs) with totally unknown weight information. These methods are based on characteristics of decision makers and uncertain decision matrices themselves, and employ such theories as attribute entropy, distance measure and fuzzy transformation for key weight information and therefore can better guarantee the efficiency and quality of group decision making under uncertainty.(3) Study on an attitudinal-based method for constructing intuitionistic fuzzy information under group decision making environment. For the difficulty in handling hybrid attribute values, the dissertation develops an attitudinal-based method for constructing intuitionistic fuzzy information in attempting to convert uncertain hybrid attribute values into unified intuitionistic fuzzy values corresponding with a decision maker's attitude which are relatively easy to handle. The presented method fully considers and formalizes a decision maker's attitude as well as preference, and can construct intuitionistic fuzzy values corresponding with a decision maker's attitude while avoiding the loss and distortion of original decision information, and therefore it has greater flexibility in practical applications.Oriented to group decision making under uncertainty, this research makes a useful exploration on the two difficult focuses under group decision making environment, i.e. combination of uncertain information and acquisition of decision factors. Finally, the dissertation summarizes the related methods proposed above to present a general solution to group decision making under uncertainty with totally unknown weight information. The achievements of this study further enrich and improve the existing decision making theories and methods, and have broad application prospects in many fields such as economics, management, and the military, etc.