Some Information Aggregation Operators And Their Applications To Multi-attribute Group Decision Making Based On Multi-granularity Two-tuple Linguistic Information

Practical decision information is hard to quantificate, because many factors such as complexity、uncertainty of objects and the ambiguity of human thoughts always place restrictions on it. Using a specified language to express it is a favorable choice. In group decision making course, treating with the same decision making problem, different decision makers are likely to use different linguistic terms of granularity to describe the object of decision-making based on his or her habit. Hence it is of high value in the practical application of the research on how to make use of aggregating operator to aggregate multi-granularity linguistic assessment information that the decision maker provides and then make better decision.In this dissertation, generalized ordered weighted averaging (GOWA) operator, induced generalized ordered weighted averaging (IGOWA) operator, power geometric averaging (PG) operator, power ordered weighted geometric averaging (POWG) operator and continuous ordered weighted harmonic averaging (C-OWH) operator are extended to accommodate two-tuple linguistic or interval two-tuple linguistic environment. A series of new operators are given, and their properties are studied. Finally, based on these operators, multi-attribute group decision-making is developed. Main jobs are as follows:In Chapter One, first of all, the author introduces the background and the current research situation of aggregating operators with multi-granularity two-tuple linguistic information. At last, the author points out the main research tasks of the article.In Chapter Two, with respect to multi-attribute decision making problems with linguistic assessment information, an approach is proposed based on two-tuple linguistic information operators. Firstly, some new aggregation operators are proposed, which are the two-tuple linguistic generalized ordered weighted averaging (T-GOWA) operator and the two-tuple linguistic induced generalized ordered weighted averaging (T-IGOWA) operator, and the properties of the operators are analyzed. Then two methods of two-tuple linguistic information multi-attribute (group) decision making based on the T-GOWA and T-IGOWA operators, by which the attribute weight information is known and the attribute information is two-tuple linguistic information, are presented.In Chapter Three, the problem of multi-granularity linguistic information aggregation is investigated. Firstly, a transformation function is given to uniform the multi-granularity linguistic information into the form of two-tuple linguistic information in basic linguistic term set. Based on the affecting from the support between the aggregation information, power geometric averaging (PG) operator, weights power geometric averaging (WPG) operator and power ordered weighted geometric averaging (POWG) operator are extended to two-tuple linguistic information environment, and two-tuple linguistic power geometric averaging (T-PG) operator, two-tuple linguistic weights power geometric averaging (T-WPG) operator and two-tuple linguistic power ordered weighted geometric averaging (T-POWG) operator are proposed. Some properties of these operators are discussed. Finally, a method of applying these relative operators to the multi-attribute group decision making, by which the attribute information is two-tuple linguistic information, is presented.In Chapter Four, the problem of multi-granularity interval linguistic information aggregation is investigated. Firstly, a transformation function is given to uniform the multi-granularity interval linguistic information into the form of interval two-tuple linguistic information in basic linguistic term set. The continuous ordered weighted harmonic (C-OWH) averaging operator is extended to accommodate multi-granularity interval linguistic environment, thus continuous interval two-tuple OWH (ITC-OWH) operator is proposed. Based on ITC-OWH operator, some new operators, such as weighted harmonic ITC-OWH (WHITC-OWH) operator, ordered weighted harmonic ITC-OWH (OWHITC-OWH) operator, combined ITC-OWH (CITC-OWH) operator, are proposed, and some properties of these operators are discussed. Finally, an approach is developed to apply these relative operators to the multi-granularity interval linguistic multi-attribute group decision making, by which the attribute weight information is known and the attribute information is interval two-tuple linguistic information,.In Chapter Five, the example analysis of methods for multi-attribute group decision making based on the relative operators, which are put forward in the last three chapters, is given to demonstrate the feasibility and practicability of the proposed methods.In Chapter Six, full text job is summed up, and the prospect of the research on multiple attribute group decision making based on multi-granularity two-tuple linguistic information is looking into the distance.