Fuzzy Logic–Based Life-Cycle Cost Analysis of Road Pavements

Abstract

Life-cycle cost analysis (LCCA) is a decision-making mechanism that can be used to determine the best road pavement option. It is prevalently applied by transport authorities. However, the effect of uncertainty that stems from the nature of the analysis is a drawback in making a proper decision because it can trigger subjectivity in decision making. Although probabilistic methods are used to overcome this problem, the large amount of data required is a disadvantage that affects the usability of such methods. This study uses the fuzzy logic technique because of the popularity of its successful analyses in decision-making problems. Among the fuzzy logic extension principles, the vertex method and the Dong, Shah, and Wong (DSW) algorithm are applied in the LCCA of road pavements. The steps of the methods are described in detail. As part of the study, a model involving a traditional probabilistic method is compared with a model based on fuzzy logic by means of a case study. Results reveal that fuzzy logic–based LCCA is a promising alternative approach for transport authorities, especially for highway agencies, in making a final decision on the type of road pavement to use.