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Large Scale Optimization

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Cover of 'Large Scale Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 Restarting Strategies for the DQA Algorithm
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    Chapter 2 Mathematical Equivalence of the Auction Algorithm for Assignment and the ∊-Relaxation (Preflow-Push) Method for Min Cost Flow
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    Chapter 3 Preliminary Computational Experience with Modified Log-Barrier Functions for Large-Scale Nonlinear Programming
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    Chapter 4 A New Stochastic/Perturbation Method for Large-Scale Global Optimization and its Application to Water Cluster Problems
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    Chapter 5 Improving the Decomposition of Partially Separable Functions in the Context of Large-Scale Optimization: a First Approach
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    Chapter 6 Gradient-Related Constrained Minimization Algorithms in Function Spaces: Convergence Properties and Computational Implications
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    Chapter 7 Some Reformulations and Applications of the Alternating Direction Method of Multipliers
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    Chapter 8 Experience with a Primal Presolve Algorithm
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    Chapter 9 A Trust Region Method for Constrained Nonsmooth Equations
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    Chapter 10 On the Complexity of a Column Generation Algorithm for Convex or Quasiconvex Feasibility Problems
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    Chapter 11 Identification of the Support of Nonsmoothness
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    Chapter 12 On Very Large Scale Assignment Problems
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    Chapter 13 Numerical Solution of Parabolic State Constrained Control Problems Using SQP- and Interior-Point-Methods
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    Chapter 14 A Global Optimization Method For Weber’s Problem With Attraction And Repulsion
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    Chapter 15 Large-Scale Diversity Minimization via Parallel Genetic Algorithms
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    Chapter 16 A Numerical Comparison of Barrier and Modified Barrier Methods For Large-Scale Bound-Constrained Optimization
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    Chapter 17 A Numerical Study of Some Data Association Problems Arising in Multitarget Tracking
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    Chapter 18 Identifying the Optimal Face of a Network Linear Program with a Globally Convergent Interior Point Method
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    Chapter 19 Solution of Large Scale Stochastic Programs with Stochastic Decomposition Algorithms
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    Chapter 20 A Simple, Quadratically Convergent Interior Point Algorithm for Linear Programming and Convex Quadratic Programming
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    Chapter 21 On Two Algorithms for Nonconvex Nonsmooth Optimization Problems in Structural Mechanics
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Title
Large Scale Optimization
Published by
Springer US, December 2013
DOI 10.1007/978-1-4613-3632-7
ISBNs
978-1-4613-3634-1, 978-1-4613-3632-7
Editors

Hager, W. W., Hearn, D. W., Pardalos, P. M.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Student > Bachelor 1 20%
Unknown 3 60%
Readers by discipline Count As %
Business, Management and Accounting 1 20%
Earth and Planetary Sciences 1 20%
Unknown 3 60%