Evolutionary Algorithms

Evolutionary algorithms is a class of randomized heuristics inspired by natural evolution. They are applied in many different contexts, in particular in optimization, and analysis of such algorithms has seen tremendous advances in recent years.

Authors: Ventura, Sebastián, Luna, José María
Covers the use of Evolutionary Computation techniques to pattern mining problems
Uses algorithms that have been integrated into the well-known WEKA software for free use
Offers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process

Multiobjective Evolutionary Algorithms and Applications provides comprehensive treatment on the design of multiobjective evolutionary algorithms and their applications in domains covering areas such as control and scheduling. Emphasizing both the theoretical developments and the practical implementation of multiobjective evolutionary algorithms, a profound mathematical knowledge is not required.

In VLSI CAD, difficult optimization problems have to be solved on a constant basis. Various optimization techniques have been proposed in the past. While some of these methods have been shown to work well in applications and have become somewhat established over the years, other techniques have been ignored.