Modelling and Optimization of Chemical Engineering Processes

In the latest years, the use of computational techniques for solving different problems is rising. In this context, engineers are faced with the difficult choice of selecting and applying the best methods suited for modelling and optimization purposes. On the other hand, there are cases when the conventional approaches are not feasible and alternative methods must be developed. This book is aimed to help engineers in the application and implementation of neural networks and bio-inspired algorithms for solving day-to-day engineering problems and specific process optimization. New techniques based on artificial neural networks, differential evolution algorithm, and artificial immune systems are presented. They have proven to be flexible and efficient, having as main advantages the generalization capability and the opportunity of providing useful information for experimental practice.