| Title |
Projection-based probabilistic linguistic multi-criteria decision-making method for new energy project selection |
| ID_Doc |
19244 |
| Authors |
Deng, MH; Zhou, XY; Wang, JQ; Li, JB; Cheng, PF |
| Title |
Projection-based probabilistic linguistic multi-criteria decision-making method for new energy project selection |
| Year |
2021 |
| Published |
Journal Of Intelligent & Fuzzy Systems, 41.0, 1 |
| DOI |
10.3233/JIFS-210573 |
| Abstract |
The development of new energy industry is a pressing issue due to the deterioration of the environment. The selection of new energy projects is a critical problem for decision makers. Incomplete and uncertain information appears in the process of new energy project selection. Compared with other linguistic expressions, probabilistic linguistic term set (PLTS) simultaneously reflects all possible linguistic terms and their corresponding weights, which conforms to the cognitive habits of people. Thus, a multi-criteria decision-making framework under PLTS environment is constructed for energy project selection. Firstly, a normalised projection model of PLTS, which considers the distance and the angle between two objects, is proposed to overcome the limitations of distance measurement. Secondly, a comprehensive weight-determination method combining the maximum deviation and expert scoring methods is developed to calculate the weight vector of the criteria. Furthermore, a projection-based VIKOR (Vigekriterijumska optimizacija i kompromisno regenje) method is established to select new energy projects, which can reflect the preferences of decision makers for group utility and individual regret. Finally, a numerical study on new energy project selection is performed to determine the validity and applicability of this method. Sensitive and comparative analyses are also conducted to reflect the rationality and feasibility of the method. |
| Author Keywords |
Multi-criteria decision-making; probabilistic linguistic term set; projection measurement; VIKOR method; new energy project selection |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000685896700109 |
| WoS Category |
Computer Science, Artificial Intelligence |
| Research Area |
Computer Science |
| PDF |
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