ORCID
https://orcid.org/0009-0002-0750-9582
Abstract
There are many uncertainties and complexities associated with maintaining Meter Gauge Railway (MGR) infrastructure, which calls for a methodical approach to decision-making. The development and application of a fuzzy-AHP-based decision support system (DSS) to select the optimal maintenance strategy for the MGR are presented in this study. The review covers research from 2013 to 2023 and focusses on the use of Multi-Criteria Decision Making (MCDM) and Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) techniques in railway infrastructure maintenance. To manage the inherent uncertainties and subjective judgements involved in maintenance decision-making, the Fuzzy-AHP methodology combines fuzzy logic with the Analytic Hierarchy Process (AHP). By assessing and prioritising maintenance strategies, this Fuzzy-Based DSS seeks to improve the MGR infrastructure's reliability, dependability, safety, and efficiency. The analysis reveals that while Fuzzy-AHP has been widely adopted for decision support in infrastructure maintenance, there remains a significant research gap in applying these systems to Meter Gauge Railways, particularly in developing regions. The review underscores the need for more targeted studies and suggests potential avenues for future research, including the exploration of hybrid DSS models and the application of advanced computational techniques. The findings offer insightful information to officials and railway operators about the efficacy of the Fuzzy-AHP-Based DSS in enhancing maintenance performance and optimising resource allocation.
Recommended Citation
Maulid, H. J. (2025). Fuzzy-AHP Based Decision Support System for the Selection of Optimal Maintenance Strategy for Meter Gauge Railway Infrastructure: A Review. Tanzania Journal of Engineering and Technology, 44(2), 358-376. https://doi.org/https://doi.org/10.52339/tjet.v44i2.1312
Publisher Name
University of Dar es Salaam
Included in
Artificial Intelligence and Robotics Commons, Electro-Mechanical Systems Commons, Industrial Engineering Commons, Numerical Analysis and Computation Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons