Abstract The Department of Rural Roads (DRR) in Thailand manages an extensive network of over 48,974 kilometers of roads. Traditionally, budget allocation for road maintenance has been primarily based on traffic volume and the International Roughness Index (IRI), often neglecting low-volume roads crucial for rural connectivity and development. To address this limitation, a decision support system (DSS) was developed, integrating the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). AHP facilitated the determination of the relative weights of economic, engineering, environmental, and social factors in road maintenance decisions. Subsequently, TOPSIS was employed to rank and prioritize road sections for maintenance based on their performance across these criteria. The DSS was evaluated using data from 724.124 kilometers of road and a budget of 4,078 million baht. The evaluation revealed that while prioritizing Benefit-Cost (B/C) Analysis resulted in a greater reduction in IRI, it often overlooked low-volume roads. In contrast, the AHP-TOPSIS method offered a more balanced approach, allocating the budget across diverse road categories and strategic objectives. The findings underscore the value of the AHP-TOPSIS-based DSS as a tool for road maintenance prioritization, particularly for agencies tasked with managing extensive road networks with varying traffic volumes and strategic importance.
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