A Novel Method of Linguistic Topsis for DMSS Technique

This paper extends the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving multi-attribute group decision making (MAGDM) problems under trapezoidal fuzzy linguistic variables. In situations where the information or the data is of the form of trapezoidal fuzzy linguistic numbers (TFLNs), some arithmetic aggregation operators have to be defined, namely the Trapezoid Fuzzy Linguistic Weighted Harmonic Averaging (TFLWHA)operator, Trapezoid Fuzzy Linguistic Ordered Weighted Harmonic Averaging (TFLOWHA) operator and Trapezoid Fuzzy Linguistic Hybrid Harmonic Averaging(TFLHHA) operator. A new method for determining decision maker?s weights is also proposed in the paper, which is used to determine the best alternative. An extended TOPSIS model is developed to solve the MAGDM problems using a new algorithm and an illustration is given

Interval-valued intuitionistic fuzzy ordered precise weighted aggregation operator and its application in group decision making

An important research topic related to the theory and application of the interval-valued intuitionistic fuzzy weighted aggregation operators is how to determine their associated weights. In this paper, we propose a precise weight-determined (PWD) method of the monotonicity and scale-invariance, just based on the new score and accuracy functions of interval-valued intuitionistic fuzzy number (IIFN). Since the monotonicity and scale-invariance, the PWD method may be a precise and objective approach to calculate the weights of IIFN and interval-valued intuitionistic fuzzy aggregation operator, and a more suitable approach to distinguish different decision makers (DMs) and experts in group decision making. Based on the PWD method, we develop two new interval-valued intuitionistic fuzzy aggregation operators, i.e. interval-valued intuitionistic fuzzy ordered precise weighted averaging (IIFOPWA) operator and interval-valued intuitionistic fuzzy ordered precise weighted geometric (IIFOPWG) operator, and study their desirable properties in detail. Finally, we provide an illustrative example. First published online: 24 Jan 201