Fuzzy-Based Methodology for Integrated Infrastructure Asset Management

• Main Authors: Mohamed Marzouk, Ahmed Osama
• Format: Article
• Language: English
• Published: Atlantis Press 2017-01-01
• Series: International Journal of Computational Intelligence Systems
• Subjects: Infrastructure Asset Management; Infrastructure Condition Assessment; Fuzzy expert system; Fuzzy/Monte Carlo Simulation; Analytical Hierarchical Process; Genetic Algorithms
• Online Access: https://www.atlantis-press.com/article/25872434/view

Most municipal agencies are facing challenges regarding the deterioration of infrastructures due to the lack of available funds and available data. There is a need to perform infrastructure asset management for infrastructure assets in an integrated manner. This research proposes a decision making plan to help the agencies to perform integrated infrastructure asset management. This research presents a methodology that helps infrastructure managers conduct their short and long terms management plans. The proposed methodology is capable to assess the condition of three infrastructure asset types including, Water networks, Sewer networks, and Road networks. Also, it is capable to assess the risk and perform the life cycle cost analysis for the integrated infrastructure assets. Factors that affect the deterioration rates of the three considered infrastructure assets types have been concluded from analyzing the literature and from gathering the expert opinions through a questionnaire sent to them. Pair-wise technique has been used to produce weight of effect of each factor at the deterioration rate. Then, a deterioration model is developed using hierarchical fuzzy expert system (HFES) technique. Another risk model is developed for assets’ failure in order to evaluate the risk associated with each segment in the network for the three infrastructure types. Fuzzy Monte Carlo Simulation (FMCS) is used to model the probability of failure (POF) and developing the risk index distribution for each type of asset. In an effort to facilitate decision-making during the rehabilitation planning, multi-objective optimization is performed, considering four objective functions; overall risk index, infrastructure’s condition, assets’ level of service and life cycle cost. A case study is considered in order to demonstrate the features of the proposed methodology.