A new potential reduction algorithm for smooth convex programming
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Publication:4944415
DOI10.1080/02331939808844411zbMath0961.90076OpenAlexW1987206661MaRDI QIDQ4944415
Publication date: 7 June 2001
Published in: Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331939808844411
Convex programming (90C25) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Variational inequalities (global problems) in infinite-dimensional spaces (58E35)
Cites Work
- A new polynomial-time algorithm for linear programming
- An \(O(n^ 3L)\) potential reduction algorithm for linear programming
- An algorithm for linear programming which requires \(O(((m+n)n^ 2+(m+n)^{1.5}n)L)\) arithmetic operations
- A polynomial-time algorithm, based on Newton's method, for linear programming
- An extension of Karmarkar's projective algorithm for convex quadratic programming
- Interior path following primal-dual algorithms. I: Linear programming
- Interior path following primal-dual algorithms. II: Convex quadratic programming
- A polynomial-time algorithm for a class of linear complementarity problems
- An \(O(\sqrt n L)\) iteration potential reduction algorithm for linear complementarity problems
- Containing and shrinking ellipsoids in the path-following algorithm
- Lagrange Multipliers and Optimality
- A Polynomial-Time Primal-Dual Affine Scaling Algorithm for Linear and Convex Quadratic Programming and Its Power Series Extension
- A Centered Projective Algorithm for Linear Programming
- Recovering optimal dual solutions in Karmarkar's polynomial algorithm for linear programming
- A Complexity Analysis for Interior-Point Algorithms Based on Karmarkar’s Potential Function
- Monotonicity of Primal and Dual Objective Values in Primal-dual Interior-point Algorithms
- Convex Analysis
- Adjustment of an Inverse Matrix Corresponding to a Change in One Element of a Given Matrix
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