Every real-world problem from economic to scientific and
engineering fields is ultimately confronted with a common task,
viz., optimization. Genetic and evolutionary algorithms (GEAs) have
often achieved an enviable success in solving optimization problems
in a wide range of disciplines. The goal of this book is to provide
effective optimization algorithms for solving a broad class of
problems quickly, accurately, and reliably by employing
evolutionary mechanisms. In this regard, five significant issues
have been investigated:
- Bridging the gap between theory and practice of GEAs, thereby
providing practical design guidelines.
- Demonstrating the practical use of the suggested road map.
- Offering a useful tool to significantly enhance the exploratory
power in time-constrained and memory-limited applications.
- Providing a class of promising procedures that are capable of
scalably solving hard problems in the continuous domain.
- Opening an important track for multiobjective GEA research that
relies on decomposition principle.
This book serves to play a decisive role in bringing forth a
paradigm shift in future evolutionary computation.
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