Many complex aeronautical design problems can be formulated with
efficient multi-objective evolutionary optimization methods and game
strategies.
This book describes the role of advanced innovative evolution tools in
the solution, or the set of solutions of single or multi disciplinary
optimization. These tools use the concept of multi-population,
asynchronous parallelization and hierarchical topology which allows
different models including precise, intermediate and approximate models
with each node belonging to the different hierarchical layer handled by
a different Evolutionary Algorithm. The efficiency of evolutionary
algorithms for both single and multi-objective optimization problems are
significantly improved by the coupling of EAs with games and in
particular by a new dynamic methodology named "Hybridized Nash-Pareto
games".
Multi objective Optimization techniques and robust design problems
taking into account uncertainties are introduced and explained in
detail. Several applications dealing with civil aircraft and UAV, UCAV
systems are implemented numerically and discussed. Applications of
increasing optimization complexity are presented as well as two hands-on
test cases problems. These examples focus on aeronautical applications
and will be useful to the practitioner in the laboratory or in
industrial design environments.
The evolutionary methods coupled with games presented in this volume can
be applied to other areas including surface and marine transport,
structures, biomedical engineering, renewable energy and environmental
problems.
This book will be of interest to students, young scientists and
engineers involved in the field of multi physics optimization.
