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.
This book focuses on systems architecture optimization. The first two parts are a concise presentation for classical optimization methods. Part three presents recent advances in systems architecture optimization. Part four outlines detailed engineering applications.
Arvustused
"The title of this book perfectly sums up the topic and scope of the text: optimization algorithms. A specialist in aerospace engineering, Abdelkhalik (Iowa State Univ.) provides a solid background review of the application domains and traditional approaches to optimization techniques. This textbook is a suitable reference for graduate students, post-docs, faculty, and engineers working on optimization algorithms to solve similar problems in the space and renewable energy sectors."
R. S. Stansbury, Embry-Riddle Aeronautical University
Preface. SECTION I: BACKGROUND AND MOTIVATION. Introduction and
Background. Modeling Examples of Variable-Size Design Space Problems. SECTION
II: CLASSICAL OPTIMIZATION. Fundamentals and Core Algorithms. Unconstrained
Optimization. Constrained Optimization. SECTION III: VARIABLE-SIZE DESIGN
SPACE OPTIMIZATION. Hidden Genes Genetic Algorithms. Structured Chromosome
Genetic Algorithms. Dynamic-Size Multiple Population Genetic Algorithms.
SECTION IV: APPLICATIONS. Space Trajectory Optimization. Optimization of Wave
Energy Converters.
Dr. Ossama Abdelkhalik is Associate Professor in the Department of Aerospace Engineering at Iowa State University. He received his PhD from Texas A&M University, College Station, TX, in Aerospace Engineering. His research interests are in Dynamics, Control, and Optimization with applications in space trajectory optimization, ocean wave energy conversion, and spacecraft dynamics. Dr. Abdelkhalik is associate fellow of AIAA, and currently a member of the AIAA technical committee on Astrodynamics.
