Fuzzy logic based life cycle cost analysis model for preventive road maintenance by considering user costs

Road maintenance programs are an important requirement so that road performance remains stable. Life cycle cost analysis (LCCA) is one of the methods in the pavement management process. LCCA is used to support decision makers as a network level analysis tool. Many transportation agencies have used deterministic and probabilistic LCCA approaches. Decision makers use the probability method to evaluate investment risk using input variables, assumptions, or uncertain estimates. Data input is ambiguous and uncertain, so the use of soft computing applications can be used. This paper discusses the development of LCCA preventive maintenance tools for road pavement using soft computing techniques. Fuzzy logic-based algorithm presents LCCA for pavement preventive maintenance by considering user costs. Algorithm with a rule-based fuzzy logic system where users can define rules to reflect agency policies and strategies. This algorithm is part of a framework that can be proposed for the use of other soft computing techniques in handling preventive maintenance of roads