Title | Large Scale Optimization [electronic resource] : State of the Art / edited by W. W. Hager, D. W. Hearn, P. M. Pardalos |
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Imprint | Boston, MA : Springer US, 1994 |
Connect to | http://dx.doi.org/10.1007/978-1-4613-3632-7 |
Descript | XIV, 456 p. online resource |
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 Weberโs 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 Convex Quadratic Programming -- On Two Algorithms for Nonconvex Nonsmooth Optimization Problems in Structural Mechanics