Separable Optimization

Stefan M. Stefanov ()
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Stefan M. Stefanov: South-West University Neofit Rilski

in Springer Optimization and Its Applications from Springer, currently edited by Pardalos, Panos, Thai, My T. and Du, Ding-Zhu

Date: 2021
Edition: 2nd ed. 2021
ISBN: 978-3-030-78401-0
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Chapters in this book:

Ch Chapter 1 Preliminaries: Convex Analysis and Convex Programming

Stefan M. Stefanov

Ch Chapter 10 Extensions

Stefan M. Stefanov

Ch Chapter 11 Applications and Computational Experiments

Stefan M. Stefanov

Ch Chapter 12 Applications of Convex Separable Unconstrained Nondifferentiable Optimization to Approximation Theory

Stefan M. Stefanov

Ch Chapter 13 About Projections in the Implementation of Stochastic Quasigradient Methods to Some Probabilistic Inventory Control Problems

Stefan M. Stefanov

Ch Chapter 14 Valid Inequalities, Cutting Planes, and Integrality of the Knapsack Polytope

Stefan M. Stefanov

Ch Chapter 15 Relaxation of the Equality Constrained Convex Continuous Knapsack Problem

Stefan M. Stefanov

Ch Chapter 16 On the Solution of Multidimensional Convex Separable Continuous Knapsack Problem with Bounded Variables

Stefan M. Stefanov

Ch Chapter 17 Characterization of the Optimal Solution of the Convex Generalized Nonlinear Transportation Problem

Stefan M. Stefanov

Ch Chapter 2 Introduction. Approximating the Separable Problem

Stefan M. Stefanov

Ch Chapter 3 Convex Separable Programming

Stefan M. Stefanov

Ch Chapter 4 Separable Programming: A Dynamic Programming Approach

Stefan M. Stefanov

Ch Chapter 5 Statement of the Main Problem. Basic Result

Stefan M. Stefanov

Ch Chapter 6 Version One: Linear Equality Constraints

Stefan M. Stefanov

Ch Chapter 7 The Algorithms

Stefan M. Stefanov

Ch Chapter 8 Version Two: Linear Constraint of the Form “ $$\ge $$ ≥ ”

Stefan M. Stefanov

Ch Chapter 9 Well-Posedness of Optimization Problems

Stefan M. Stefanov

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DOI: 10.1007/978-3-030-78401-0

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