An Integrated Single-Valued Neutrosophic Combined Compromise Solution Methodology for Renewable Energy Resource Selection Problem

Energies

Raghunathan Krishankumar¹  Jabir Ali²  Fausto Cavallaro³  Arunodaya Raj Mishra⁴  Pratibha Rani⁵  Kattur S. Ravichandran⁶ 

[1] Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore 641112, Tamil Nadu, India;Department of Computer Science and Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, NCR Campus, Ghaziabad 201204, Uttar Pradesh, India;Department of Economics, University of Molise, 86100 Campobasso, Italy;Department of Mathematics, Government College Jaitwara, Jaitwara 485221, Madhya Pradesh, India;Department of Mathematics, National Institute of Technology, Warangal 506004, Telangana, India;Rajiv Gandhi National Institute of Youth Development, Sriperumbudur 602105, Tamil Nadu, India;

关键词: single-valued neutrosophic set;    MCDM;    SWARA;    CoCoSo;    renewable energy source selection;   

DOI  :  10.3390/en14154594

来源: DOAJ

【 摘 要 】

Optimal renewable energy source (RES) selection needs a strategic decision for reducing environmental pollutions, use of conventional resources, and improving economic development. In the process of RESs evaluation, several aspects like environmental, economic, social, and technical requirements play an important role. In addition, diverse factors affect the appropriate RES selection problem which adheres to uncertain and imprecise data. Thus, this selection process can be considered as a complex uncertain multi-criteria decision making (MCDM) problem. This study aims to introduce a novel integrated methodology based on Step-wise Weight Assessment Ratio Analysis (SWARA) and Combined Compromise Solution (CoCoSo) methods within single-valued neutrosophic sets (SVNSs) context, wherein the decision-makers and criteria weights are completely unknown. In the proposed approach, the criteria weights are determined by the SWARA method, and the most suitable RES alternative is determined by an improved CoCoSo method under the SVN context. Further, an illustrative case study of RES selection is considered to demonstrate the thorough execution process of the proposed method. Moreover, a comparison with existing methods is discussed to analyze the validity of the obtained result. This study performs sensitivity analysis with a various set of criteria weights to reveal the robustness of the developed approach. The strength of the proposed method is its practical applicability and ability to provide solutions under uncertain, imperfect, indeterminate, and inconsistent information.

【 授权许可】

Unknown