This book describes how to use computational intelligence and artificial
intelligence tools to improve the decision-making process in new product
development. These approaches, including artificial neural networks and
constraint satisfaction solutions, enable a more precise prediction of
product development performance compared to widely used multiple
regression models. They support decision-makers by providing more
reliable information regarding, for example, project portfolio selection
and project scheduling.
The book is appropriate for computer scientists, management scientists,
students and practitioners engaged with product innovation and
computational intelligence applications.