Optimizing Algorithm for Reliability ASsessment of Radial Lifeline Systems

A prominent reason for finding efficient methods to quantify reliability of radial lifeline systems may be attributed to the susceptibility of large scale failure when a single line segment in the system fails. Proposed methods include Monte Carlo simulation techniques and probabilistic recursive algorithms, which are traditionally limited in their computational efficiency, accuracy, and full analysis of the general case radial lifeline system. This study proposes an algorithm for calculating the complete probability distribution of customer service availability (CSA) for the general case for radial lifeline systems, and explores the sensitivity of components to large scale failure.