The book consists of four parts. The first part is dedicated to classical methods and further to the theory and applications of classical optimization methods. Here are research papers that discuss, for example, dynamic optimization using analytic and evolutionary approaches and compare two different approaches or a chapter discussing bounded dual simplex algorithm. The application part discusses the intersection of bio-inspired optimization and game theory amongst others.
The heuristic part is significantly bigger and also divided into two parts, again being theory and applications. In the theoretical part can be found chapters about genetic programming, differential evolution, automatic design and optimization of fuzzy inference systems or relations between complex networks and dynamics of evolutionary algorithms. Lastly, the application part, contain chapters that discuss the use of evolutionary algorithms in a wide range of applications from evolutionary algorithms based on game theory and cellular automata with coalitions to chaotic systems control. The book is based on original research and contains all important results.