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Exploring the integration of multi criteria decision analysis in the clean energy biodiesels applications: A systematic review and gap analysis.

Authors :
Alamoodi, A.H.
Garfan, Salem
Al-Zuhairi, Omar
Zaidan, B.B.
Zaidan, A.A.
Albahri, O.S.
Y.Y. Ahmaro, Ibraheem
Albahri, A.S.
Yussof, Salman
Magableh, Aws A.
Source :
Engineering Applications of Artificial Intelligence. Jul2024:Part A, Vol. 133, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Biodiesel has gained tremendous attention from researchers due to its environmentally friendly and renewable fuel manufactured domestically from vegetable oils or animal fats. Multiple factors, including emission and fuel efficiency, measure the performance of biodiesel. These characteristics make the process of evaluation and benchmarking a multi-criteria decision-making (MCDM) problem. This research attempts to survey the literature for multi-criteria decision-making applications on biodiesel. This systematic review was carried out on four scientific databases: PubMed, ScienceDirect, IEEE Xplore, and WoS. The collected articles were summarized and mapped into a coherent taxonomy, while the main challenges, motivations, and recommendations were collected and categorized for better understanding and finding out essential characteristics. The final set of included articles was 33, and they were categorized into six different categories. Most articles (n=15/33) investigated the evaluation and selection of biodiesel alternatives using MCDM. Furthermore, a state-of-art bibliometric analysis is provided. The analysis demonstrates several challenges in this area, such as source selection, optimum fuel blending, and uncertainty. This article is expected to assist future researchers in addressing the current gaps and contribute to advancing this area. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09521976
Volume :
133
Database :
Academic Search Index
Journal :
Engineering Applications of Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
177605405
Full Text :
https://doi.org/10.1016/j.engappai.2024.108023