Optimization Theory and Applications: DE (Advanced Lectures in Mathematics) - Softcover

Inhaltsangabe

§ 1 Introduction, Examples, Survey.- 1.1 Optimization problems in elementary geometry.- 1.2 Calculus of variations.- 1.3 Approximation problems.- 1.4 Linear programming.- 1.5 Optimal Control.- 1.6 Survey.- 1.7 Literature.- § 2 Linear Programming.- 2.1 Definition and interpretation of the dual program.- 2.2 The FARKAS-Lemma and the Theorem of CARATHEODORY.- 2.3 The strong duality theorem of linear programming.- 2.4 An application: relation between inradius and width of a polyhedron.- 2.5 Literature.- § 3 Convexity in Linear and Normed Linear Spaces.- 3.1 Separating convex sets in linear spaces.- 3.2 Separation of convex sets in normed linear spaces.- 3.3 Convex functions.- 3.4 Literature.- § 4 Convex Optimization Problems.- 4.1 Examples of convex optimization problems.- 4.2 Definition and motivation of the dual program. The weak duality theorem.- 4.3 Strong duality, KUHN-TUCKER saddle point theorem.- 4.4 Quadratic programming.- 4.5 Literature.- § 5 Necessary Optimality Conditions.- 5.1 GATEAUX and FRECHET Differential.- 5.2 The Theorem of LYUSTERNIK.- 5.3 LAGRANGE multipliers. Theorems of KUHN-TUCKER and F. JOHN type.- 5.4 Necessary optimality conditions of first order in the calculus of variations and in optimal control theory.- 5.5 Necessary and sufficient optimality conditions of second order.- 5.6 Literature.- § 6 Existence Theorems for Solutions of Optimization Problems.- 6.1 Functional analytic existence theorems.- 6.2 Existence of optimal controls.- 6.3 Literature.- Symbol Index.

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