The European Community on Computational Methods in Applied Science (ECCOMAS) has been created with the aim of providing a co-ordination of international scientific conferences and other activities in the field of computational methods in applied sciences. The main objective of the joint conferences on computational fluid dynamics and numerical methods in engineering is to provide a common forum for the presentation and discussion of scientific computing applied to engineering sciences. Equal emphasis is to be given to basic methodologies, scientific developments and industrial applications. These conferences are presented in three volumes. Volume one, Computational Fluid Dynamics '96, covers the proceedings of the Third ECCOMAS Conference on Computational Fluid Dynamics; Volume two, Numerical Methods in Engineering '96, covers the proceedings of the second ECCOMAS Conference on Numerical Methods in Engineering; and Volume three, Computational Methods in Applied Sciences '96, which presents invited lectures and special technical sessions of both the Third ECCOMAS Computational Fluid Dynamics Conference and the Second ECCOMAS Conference on Numerical Methods in Engineering.

This book provides research results using computational methods for fluid dynamics and engineering problems in aeronautics and other scientific and industrial applications. It gives an overview on the state of the art and the technology trends requiring advanced computational methods towards digitization in industrial and scientific processes. The chapters are based on Special Technology Sessions of the WCCM-ECCOMAS Virtual Congress 2021.

This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.