New group decision making method in intuitionistic fuzzy setting based on TOPSIS

Abstract

In multiple attribute group decision making, the weights of decision makers are very crucial to ranking results and have gained more and more attentions. A new approach to determining experts’ weights is proposed based on the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method in intuitionistic fuzzy setting. The weights determined by our method have two advantages: the evaluation value has a large weight if it is close to the positive ideal evaluation value and far from negative ideal evaluation values at the same time, otherwise it is assigned a small weight; experts have different weights for different attributes, which are more appropriate for real decision making problems since each expert has his/her own knowledge and expertise. The multiple attribute intuitionistic fuzzy group decision making algorithm has been proposed which is suitable for different situations about the attribute weight information, including the attribute weights are known exactly, partly known and unknown completely. A supplier selection problem and the evaluation of murals in a metro line are finally used to illustrate the feasibility, efficiency and practical advantages of the developed approaches.

Keywords:

• multiple attribute group decision making
• intuitionistic fuzzy set
• TOPSIS
• weight

Additional information

Notes on contributors

Wei Yang

Wei YANG. Doctor, Associated Professor at Department of Mathematics, School of Science, Xi'an University of Architecture and Technology. She has contributed over 20 journal articles to professional journals such as Knowledge-Based Systems, Expert Systems with Applications, Applied Mathematical Modelling, etc. Her current research interests include multi-criteria decision making, computing with words, and information sciences.

Zhiping Chen

Zhiping CHEN. Doctor, Professor and Vice-dean at the School of Mathematics and Statistics, Xi'an Jiaotong University. He is the Standing Committee and Executive Director of the Financial Engineering and Financial Risk Management, Branch of the Operations Research Society of China. Dr Chen has published more than 100 scientific articles and 2 books, his research interests include stochastic optimization, risk management and financial optimization, operations research and its application.

Fang Zhang

Fang ZHANG. Master, Lecturer at the School of Mathematics and Statistics, Xi'an Jiaotong University. She has published 6 scientific articles, her research interests include robust optimization and financial optimization.