A novel method for hybrid multiple attribute decision making |
| |
| Authors: | Liu Pei-de |
| |
| Affiliation: | 1. Business School, Sichuan University, Chengdu 610064, China;2. Department of Computer Science and Artificial Intelligence, University of Granada, Granada 18071, Spain;3. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China;4. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia;1. Business School, Sichuan University, Chengdu 610064, China;2. Andalusian Research Institute on Data Science and Computational Intelligence (DaSCI), University of Granada, Granada 18071, Spain;3. Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia;1. College of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, China;2. College of Science, Guilin University of Technology, Guilin 541004, China;3. School of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013, China;1. Business School, Sichuan University, Chengdu 610064, China;2. Department of Computer Science and Artificial Intelligence, University of Granada, E-18071 Granada, Spain |
| |
| Abstract: | An approach based on 2-tuple is presented to solve the hybrid multiple attribute decision making problem with weight information unknown. First, transformation rules between linguistic variables and triangular fuzzy numbers, and distance between 2-tuple linguistics are defined, then the transformation method between 2-tuple linguistic and different forms of indicator values is given. Besides, according to grey incidence minimum deviation theory of positive ideal solution, the weights of indicators are determined, and then alternatives are ranked by 2-tuple linguistic weighting arithmetic average values. Finally, an illustrative example is given to demonstrate the procedure of the method and to compare with TOPSIS method to show the effectiveness and advantages of the presented method. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
