The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance

Main Article Content

Ali Ezzat Hasan
Firas Khairy Jaber

Abstract

Priority of road maintenance can be viewed as a process influenced by decision-makers with varying decision-making power. Each decision-maker may have their view and judgment depending on their function and responsibilities. Therefore, determining the priority of road maintenance can be thought of as a process of MCDM. Regarding the priority of road maintenance, this is a difficult MCDM problem involving uncertainty, qualitative criteria, and possible causal relationships between choice criteria. This paper aims to examine the applicability of multiple MCDM techniques, which are used for assessing the priority of road maintenance, by adapting them to this sector. Priority of road maintenance problems subject to internal uncertainty caused by imprecise human judgments will be reviewed and investigated, as well as the most popular theories and methods in group MCDM for presenting uncertain information, creating weights for decision criteria, examining causal relationships, and ranking alternatives. The study concluded that through the strengths and weaknesses reached, fuzzy set theory is the most appropriate and best used in modeling uncertain information. In addition, the methods that are employed the most common in the literature that has been done to explore the correlations between decision criteria have been examined, and it is concluded that the fuzzy best-worst method may be utilized in this research. The Fuzzy VIKOR approach is most likely the best method for ranking the decision alternatives. 

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“The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance” (2023) Journal of Engineering, 29(10), pp. 106–125. doi:10.31026/j.eng.2023.10.07.
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How to Cite

“The Applicability of Multiple MCDM Techniques for Implementation in the Priority of Road Maintenance” (2023) Journal of Engineering, 29(10), pp. 106–125. doi:10.31026/j.eng.2023.10.07.

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