A probabilistic analysis of the simplex method
A probabilistic analysis of the simplex method
Steepest-edge simplex algorithms for linear programming
Mathematical Programming: Series A and B
A practical geometrically convergent cutting plane algorithm
SIAM Journal on Numerical Analysis
Mathematical Programming: Series A and B
New variants of bundle methods
Mathematical Programming: Series A and B
Solving Real-World Linear Programs: A Decade and More of Progress
Operations Research
Computational Techniques of the Simplex Method
Computational Techniques of the Simplex Method
A Piecewise Linear Dual Phase-1 Algorithm for the Simplex Method
Computational Optimization and Applications
Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time
Journal of the ACM (JACM)
Progress in the dual simplex method for large scale LP problems: practical dual phase 1 algorithms
Computational Optimization and Applications
Computational Optimization and Applications
A proximal cutting plane method using Chebychev center for nonsmooth convex optimization
Mathematical Programming: Series A and B
New Formulations for Optimization under Stochastic Dominance Constraints
SIAM Journal on Optimization
Generalized upper bounding techniques
Journal of Computer and System Sciences
Computational experience with linear optimization and related problems
Computational experience with linear optimization and related problems
Processing second-order stochastic dominance models using cutting-plane representations
Mathematical Programming: Series A and B
Efficient nested pricing in the simplex algorithm
Operations Research Letters
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We show that the simplex method can be interpreted as a cutting-plane method, assuming that a special pricing rule is used. This approach is motivated by the recent success of the cutting-plane method in the solution of special stochastic programming problems.We focus on the special linear programming problem of finding the largest ball that fits into a given polyhedron. In a computational study we demonstrate that ball-fitting problems have such special characteristics which indicate their utility in regularization schemes.