This book compiles recent advances of evolutionary algorithms in
dynamic and uncertain environments within a unified framework. The
book is motivated by the fact that some degree of uncertainty is
inevitable in characterizing any realistic engineering systems.
Discussion includes representative methods for addressing major
sources of uncertainties in evolutionary computation, including
handle of noisy fitness functions, use of approximate fitness
functions, search for robust solutions, and tracking moving
optimums.
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