A new decision approach for the sustainable transport investment selection based on the generalized entropy and knowledge measure under an interval-valued Pythagorean fuzzy environment

Aghamohagheghi, Mahnaz; Hashemi, Seyed Mehdi; Tavakkoli-Moghaddam, Reza

doi:10.24200/sci.2019.50131.1529

A new decision approach for the sustainable transport investment selection based on the generalized entropy and knowledge measure under an interval-valued Pythagorean fuzzy environment

Document Type : Article

Authors

¹ Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran

² Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran,

³ School of Industrial Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran, Iran

10.24200/sci.2019.50131.1529

Abstract

Finding the most suitable transport project is one of the most important tasks in transport planning. This task gets more complicated as the sustainable criteria get involved in the process. In this paper, a new multi-criteria group decision-making method with unknown expert and attribute weights is proposed to address the sustainable transport investment selection problem. To make the method more powerful in dealing with uncertain elements, an Interval-Valued Pythagorean Fuzzy (IVPF) set is used as an attractive and useful tool to handle uncertainty. First, a generalized entropy measure under an IVPF environment is introduced, which enables the method to determine the fuzziness of the attribute values, which are expressed by Interval-Valued Pythagorean Fuzzy Numbers (IVPFNs). To determine the fuzziness of IVPFNs with identical membership and non-membership degrees, a generalized knowledge measure of the IVPFNs is also introduced. Based on this measure and considering the deviation between attribute assessments, a new optimization model is presented to obtain unknown attribute weights. In addition, based on the extension of the VIKOR method, a new algorithm is presented to determine the unknown expert weights. Finally, a real case study is considered to show the efficiency of the proposed methods.

Keywords