All Areas Submissions - January 2001
Applications — Science and Engineering
Improved linear programming bounds for antipodal spherical codes
Kurt M. Anstreicher
Integer Programming
Generating Convex Polynomial Inequalities for Mixed 0-1 Programs
Robert Stubbs, Sanjay Mehrotra
Convex and Nonsmooth Optimization
Two properties of condition numbers for convex programs via implicitly defined barrier functions
Javier Pena
Applications — OR and Management Sciences
Frequency Planning and Ramifications of Coloring
Andreas Eisenblaetter, Martin Groetschel, Arie M.C.A. Koster
Applications — OR and Management Sciences
Re-Optimization of Signaling Transfer Points
Arie M.C.A. Koster
Other Topics
Generalized Goal Programming: Polynomial Methods and Applications
Emilio Carrizosa, Joerg Fliege
Combinatorial Optimization
GRASP: An annotated bibliography
P. Festa, M. G. C. Resende
Nonlinear Optimization
Reducing the number of AD passes for computing a sparse Jacobian matrix
Shahadat Hossain, Trond Steihaug
Applications — Science and Engineering
Optimal Control of Distributed Proceses using Reduced Order Models
Eva Balsa-Canto, Antonio A. Alonso, Julio R. Banga
Linear, Cone and Semidefinite Programming
An Interior-Point Approach to Sensitivity Analysis in Degenerate Linear Programs
E. Alper Yildirim, Michael J. Todd
Convex and Nonsmooth Optimization
Non Convergence Result for Conformal Approximation of
Variational Problems Subject to a Convexity Constraint
Philippe Choné, Hervé Le Meur
Network Optimization
Newton Algorithms for Large-Scale Strictly Convex Separable Network Optimization
Aleksandar Donev, Phillip Duxbury
Applications — Science and Engineering
Handling Nonnegative Constraints in Spectral Estimation
Brien Alkire, Lieven Vandenberghe
Convex and Nonsmooth Optimization
Convex optimization problems involving finite autocorrelation sequences
Brien Alkire, Lieven Vandenberghe
Applications — OR and Management Sciences
Optimal location of intermodal freight hubs
Illia Racunica, Laura Wynter
Linear, Cone and Semidefinite Programming
A New and Efficient Large-Update Interior-Point Method for Linear Optimization
J Peng, C Roos, T Terlaky
Applications — OR and Management Sciences
On some difficult linear programs coming from Set Partitioning
Francisco Barahona, ranga anbil
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