Memetic algorithms are evolutionary algorithms that apply a
local search process to refine solutions to hard problems. Memetic
algorithms are the subject of intense scientific research and have
been successfully applied to a multitude of real-world problems
ranging from the construction of optimal university exam
timetables, to the prediction of protein structures and the optimal
design of space-craft trajectories. This monograph presents a rich
state-of-the-art gallery of works on memetic algorithms. Recent
Advances in Memetic Algorithms is the first book that focuses on
this technology as the central topical matter. This book gives a
coherent, integrated view on both good practice examples and new
trends including a concise and self-contained introduction to
memetic algorithms. It is a necessary read for postgraduate
students and researchers interested in recent advances in search
and optimization technologies based on memetic algorithms, but can
also be used as complement to undergraduate textbooks on artificial
intelligence.
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