Real-World Applications of Genetic Algorithms

The book addresses some of the most recent, with theoretical and methodological aspects, scalable multi-objective optimization problems and various design challenges by using different combined intelligence approaches. Multi-objective optimization has been around for about two decades, and its application to real-world problems continues to grow. In addition, many applications operate more efficiently using a hybrid systems approach.

The book presents hybrid techniques based on artificial neural networks, fuzzy sets, automatic theory, other classical or hyper-simulation algorithms, and more. The book looks at various examples of algorithms in various real-world application areas such as histogram growth problem, speech synthesis, provider problem, scheduling problem, antenna design, gene design, chemical and biochemical process modeling, etc.