Many systems architecture optimization problems are characterized
by a variable number of optimization variables. Many classical
optimization algorithms are not suitable for such problems. The
book presents recently developed optimization concepts that are
designed to solve such problems. These new concepts are implemented
using genetic algorithms and differential evolution. The examples
and applications presented show the effectiveness of the use of
these new algorithms in optimizing systems architectures. The book
focuses on systems architecture optimization. It covers new
algorithms and its applications, besides reviewing fundamental
mathematical concepts and classical optimization methods. It also
provides detailed modeling of sample engineering problems. The book
is suitable for graduate engineering students and engineers. The
second part of the book includes numerical examples on classical
optimization algorithms, which are useful for undergraduate
engineering students. While focusing on the algorithms and their
implementation, the applications in this book cover the space
trajectory optimization problem, the optimization of earth orbiting
satellites orbits, and the optimization of the wave energy
converter dynamic system: architecture and control. These
applications are illustrated in the starting of the book, and are
used as case studies in later chapters for the optimization methods
presented in the book.
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