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SDPT3 -- A Matlab Software Package for Semidefinite Programming
This invention relates to stabilizing compositions that comprises a vinyl chloride or vinylidene chloride homopolymer or copolymer and a stabilizing amount of an organotin halide exhibiting the formula RSnX3.
Solving semidefinite-quadratic-linear programs using SDPT3
Computational experiments with linear optimization problems involving semidefinite, quadratic, and linear cone constraints (SQLPs) are discussed and computational results on problems from the SDPLIB and DIMACS Challenge collections are reported.
Self-Scaled Barriers and Interior-Point Methods for Convex Programming
This paper provides a theoretical foundation for efficient interior-point algorithms for convex programming problems expressed in conic form, when the cone and its associated barrier are self-scaled, with long-step and symmetric primal-dual methods.
Primal-Dual Interior-Point Methods for Self-Scaled Cones
This paper presents efficiency estimates for several symmetric primal-dual methods that can loosely be classified as path-following methods for convex programming problems expressed in conic form when the cone and its associated barrier are self-scaled.
- M. Todd
- Computer ScienceHandbook of Discrete and Computational Geometry…
The Computation of Fixed Points and Applications
- M. Todd
- 9 June 1976
I Brouwer's Theorem.- II Some Applications of Brouwer's Theorem.- III Triangulations.- IV Algorithms to Find Completely-Labelled Simplices.- V Extensions of Brouwer's Theorem.- VI Applications of…
The development of distance-weighted discrimination, which is based on second-order cone programming, a modern computationally intensive optimization method, is developed.
On the Nesterov-Todd Direction in Semidefinite Programming
How the search directions for the Nesterov--Todd (NT) method can be computed efficiently and how they can be viewed as Newton directions are discussed and demonstrated.
On the Implementation and Usage of SDPT3 – A Matlab Software Package for Semidefinite-Quadratic-Linear Programming, Version 4.0
Numerical experiments show that this general-purpose code can solve more than 80% of a total of about 430 test problems to an accuracy of at least 10 − 6 in relative duality gap and infeasibilities.
On Adaptive-Step Primal-Dual Interior-Point Algorithms for Linear Programming
Heuristic reasoning is provided for expecting that the algorithms will perform much better in practice than guaranteed by the worst-case estimates, based on an analysis using a nonrigorous probabilistic assumption.