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.
General
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