Theory of linear and integer programming
Theory of linear and integer programming
On the complexity of approximating extremal determinants in matrices
Journal of Complexity
Parallel Optimization: Theory, Algorithms and Applications
Parallel Optimization: Theory, Algorithms and Applications
Fast Heuristics for the Maximum Feasible Subsystem Problem
INFORMS Journal on Computing
A simple polynomial-time rescaling algorithm for solving linear programs
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
Randomized relaxation methods for the maximum feasible subsystem problem
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Randomized relaxation methods for the maximum feasible subsystem problem
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
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A classical theorem by Block and Levin (Block, H. D., S. A. Levin. 1970. On the boundedness of an iterative procedure for solving a system of linear inequalities. Proc. Amer. Math. Soc.26 229-235) states that certain variants of the relaxation method for solving systems of linear inequalities generate bounded sequences of intermediate solutions, even when applied to infeasible systems. Using a new approach, we prove a more general version of this result and answer an old open problem of quantifying the bound as a function of the input data.