Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, Second Edition
by Amir Beck
Introduction to Nonlinear Optimization offers a structured treatment of the theory, algorithms, and applications of nonlinear optimization. With examples and computational work in Python and MATLAB, this second edition connects mathematical foundations with practical implementation for students, researchers, and practitioners exploring optimization methods.
About This Book
Introduction to Nonlinear Optimization presents the theory and methods of nonlinear optimization in a structured format.
The book combines foundational concepts with algorithms, helping readers connect mathematical ideas to computational procedures.
Applications and programming examples using Python and MATLAB provide a practical dimension to the subject.
This second edition is suited to readers developing an understanding of nonlinear optimization and its use in technical and quantitative settings.
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