09-23-2026, 08:40 PM
Practical Optimization by Philip E. Gill, Walter Murray, and Margaret H. Wright is a comprehensive treatment of numerical optimization, originally published in 1981 and republished by SIAM in 2019. The book develops the mathematical foundations needed to formulate and solve optimization problems, beginning with objective functions, constraints, numerical errors, and optimality conditions. It then progresses through unconstrained optimization, problems with linear constraints, and more difficult nonlinear constraints, emphasizing both the mathematical reasoning behind algorithms and their computational implementation.
A major strength of the book is its practical algorithmic perspective: it provides step-by-step descriptions and pseudocode rather than treating optimization purely theoretically. The later chapters address mathematical modeling and the practical difficulties encountered when implementing optimization methods, including numerical issues and strategies for dealing with real-world problems.
Although many developments in optimization have occurred since the original edition, SIAM notes that the fundamental principles and intuition remain relevant, including for modern applications in data science, large-scale computation, and machine learning,
BOOK
A major strength of the book is its practical algorithmic perspective: it provides step-by-step descriptions and pseudocode rather than treating optimization purely theoretically. The later chapters address mathematical modeling and the practical difficulties encountered when implementing optimization methods, including numerical issues and strategies for dealing with real-world problems.
Although many developments in optimization have occurred since the original edition, SIAM notes that the fundamental principles and intuition remain relevant, including for modern applications in data science, large-scale computation, and machine learning,
BOOK
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