This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively. The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization. The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

Yan-Fu Li is Full Professor at the Department of Industrial Engineering and the Director of the Institute for Quality & Reliability at Tsinghua University, China. He received his Ph.D in Industrial Engineering from National University of Singapore in 2010 Enrico Zio is Full Professor at Mines-Paris, PSL University, and at the Energy Department of Politecnico di Milano, Italy. He received his Ph.D in nuclear engineering from Politecnico di Milano and in Probabilistic Risk Assessment from MIT in 1996 and 1998, respectively.

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