This textbook provides students, researchers, and engineers in the area
of electrical engineering with advanced mathematical optimization
methods. Presented in a readable format, this book highlights
fundamental concepts of advanced optimization used in electrical
engineering. Chapters provide a collection that ranges from simple yet
important concepts such as unconstrained optimization to highly advanced
topics such as linear matrix inequalities and artificial
intelligence-based optimization methodologies. The reader is motivated
to engage with the content via numerous application examples of
optimization in the area of electrical engineering. The book begins with
an extended review of linear algebra that is a prerequisite to
mathematical optimization. It then precedes with unconstrained
optimization, convex programming, duality, linear matrix inequality, and
intelligent optimization methods. This book can be used as the main text
in courses such as Engineering Optimization, Convex Engineering
Optimization, Advanced Engineering Mathematics and Robust Optimization
and will be useful for practicing design engineers in electrical
engineering fields. Author provided cases studies and worked examples
are included for student and instructor use.