Overview

On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied Optimization, was held at the University of Florida. The con­ ference was supported by the National Science Foundation, the U. S. Army Research Office, and the University of Florida, with endorsements from SIAM, MPS, ORSA and IMACS. Forty one invited speakers presented papers on mathematical program­ ming and optimal control topics with an emphasis on algorithm development, real world applications and numerical results. Participants from Canada, Japan, Sweden, The Netherlands, Germany, Belgium, Greece, and Denmark gave the meeting an important international component. At­ tendees also included representatives from IBM, American Airlines, US Air, United Parcel Serice, AT & T Bell Labs, Thinking Machines, Army High Performance Com­ puting Research Center, and Argonne National Laboratory. In addition, the NSF sponsored attendance of thirteen graduate students from universities in the United States and abroad. Accurate modeling of scientific problems often leads to the formulation of large­ scale optimization problems involving thousands of continuous and/or discrete vari­ ables. Large scale optimization has seen a dramatic increase in activities in the past decade. This has been a natural consequence of new algorithmic developments and of the increased power of computers. For example, decomposition ideas proposed by G. Dantzig and P. Wolfe in the 1960's, are now implement able in distributed process­ ing systems, and today many optimization codes have been implemented on parallel machines.

Full Product Details

Author:   William W. Hager ,  D.W. Hearn ,  Panos M. Pardalos
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of the original 1st ed. 1994
Dimensions:   Width: 16.00cm , Height: 2.40cm , Length: 24.00cm
Weight:   0.754kg
ISBN:  

9781461336341

ISBN 10:   1461336341
Pages:   456
Publication Date:   15 November 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Restarting Strategies for the DQA Algorithm.- Mathematical Equivalence of the Auction Algorithm for Assignment and the ?-Relaxation (Preflow-Push) Method for Min Cost Flow.- Preliminary Computational Experience with Modified Log-Barrier Functions for Large-Scale Nonlinear Programming.- A New Stochastic/Perturbation Method for Large-Scale Global Optimization and its Application to Water Cluster Problems.- Improving the Decomposition of Partially Separable Functions in the Context of Large-Scale Optimization: a First Approach.- Gradient-Related Constrained Minimization Algorithms in Function Spaces: Convergence Properties and Computational Implications.- Some Reformulations and Applications of the Alternating Direction Method of Multipliers.- Experience with a Primal Presolve Algorithm.- A Trust Region Method for Constrained Nonsmooth Equations.- On the Complexity of a Column Generation Algorithm for Convex or Quasiconvex Feasibility Problems.- Identification of the Support of Nonsmoothness.- On Very Large Scale Assignment Problems.- Numerical Solution of Parabolic State Constrained Control Problems using SQP- and Interior-Point-Methods.- A Global Optimization Method For Weber’s Problem With Attraction and Repulsion.- Large-Scale Diversity Minimization via Parallel Genetic Algorithms.- A Numerical Comparison of Barrier and Modified Barrier Methods for Large-Scale Bound-Constrained Optimization.- A Numerical Study of Some Data Association Problems Arising in Multitarget Tracking.- Identifying the Optimal Face of a Network Linear Program with a Globally Convergent Interior Point Method.- Solution of Large Scale Stochastic Programs with Stochastic Decomposition Algorithms.- A Simple, Quadratically Convergent Interior Point Algorithm for Linear Programming and ConvexQuadratic Programming.- On Two Algorithms for Nonconvex Nonsmooth Optimization Problems in Structural Mechanics.

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