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The design of modern engineering systems requires many trade-offs between the several target requirements needed along the system life. Each chapter of this book uses an innovative computing technique to elegantly solve a different engineering problem.

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The design of most modern engineering systems entails the consideration of a good trade-off between the several targets requirements to be satisfied along the system life such as high reliability, low redundancy and low operational costs. These aspects are often in conflict with one another, hence a compromise solution has to be sought. Innovative computing techniques, such as genetic algorithms, swarm intelligence, differential evolution, multi-objective evolutionary optimization, just to name few, are of great help in founding effective and reliable solution for many engineering problems. Each chapter of this book attempts to using an innovative computing technique to elegantly solve a different engineering problem.

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1- A discrete differential evolution approach with local search for traveling salesman problems.-

2- Genetic Algorithm based Reliability Optimization in Interval Environment.-

3- PSO for Building Fuzzy Systems.-

4- Maintenance optimization of wind turbine systems based on intelligent prediction tools.-

5- Clonal selection algorithm applied to economic dispatch optimization of electrical energy.-

6- Dynamic Objectives Aggregation Methods in Multi-objective Evolutionary Optimization.-

7- Application Mapping for Efficient NoC-based Implementation using Evolutionary Multi-objective Optimization.-

8- Theory and Applications of Chaotic Optimization Methods.

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