Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. This book provides effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms.
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.