A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory.
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A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory. Many problems arising in diverse fields such as machine learning, medicine, chemical engineering, structural design, and scheduling can be reduced to a constrained optimization problem. Provides readers with the fundamentals needed to study and solve such problems.
Preface to the Classic Edition; 1. The Nonlinear Programming Problem, Preliminary Concepts, and Notation; 2. Linear Inequalities and Theorems of the Alternative; 3. Convex Sets in Rn; 4. Convex and Concave Functions; 5. Saddlepoint Optimality Criteria in Nonlinear Programming Without Differentiability; 6. Differentiable Convex and Concave Functions; 7. Optimality Criteria in Nonlinear Programming with Differentiability; 8. Duality in Nonlinear Programming; 9. Generalizations of Convex Functions. Quasiconvex, Strictly Quasiconvex, and Pseudoconvex Functions; 10. Optimality and Duality for Generalized Convex and Concave Functions; 11. Optimality and Duality in the Presence of Nonlinear Equality Constraints; Appendix A. Vectors and Matrices; Appendix B. Resume of Some Topological Properties of Rn; Appendix C. Continuous and Semicontinuous Functions, Minima and Infima; Appendix D. Differentiable Functions, Mean-value and Implicit Function Theorems; Bibliography; Name Index; Subject Index.
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Da: Better World Books, Mishawaka, IN, U.S.A.
Condizione: Good. Used book that is in clean, average condition without any missing pages. Codice articolo 15882747-6
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