Enhancements of ANALYZE: a computer-assisted analysis system for linear programming
ACM Transactions on Mathematical Software (TOMS)
MINOS(IIS): infeasibility analysis using MINOS
Computers and Operations Research
Some perturbation theory for linear programming
Mathematical Programming: Series A and B
Analyzing infeasible nonlinear programs
Computational Optimization and Applications
The complexity and approximability of finding maximum feasible subsystems of linear relations
Theoretical Computer Science
Detecting IIS in infeasible linear programmes using techniques from goal programming
Computers and Operations Research
Ill-Posedness and the Complexity of Deciding Existence of Solutionsto Linear Programs
SIAM Journal on Optimization
Understanding the Geometry of Infeasible Perturbations of a Conic Linear System
SIAM Journal on Optimization
On Optimal Correction of Inconsistent Linear Constraints
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Analyzing Infeasible Mixed-Integer and Integer Linear Programs
INFORMS Journal on Computing
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Computers and Operations Research
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This paper addresses the problem of finding an optimal correction of an inconsistent linear system, where only the nonzero coefficients of the constraint matrix are allowed to be perturbed for reconstructing a consistent system. Using the Frobenius norm as a measure of the distance to feasibility, a nonconvex minimization problem is formulated, whose objective function is a sum of fractional functions. A branch-and-bound algorithm for solving this nonconvex program is proposed, based on suitably overestimating the denominator function for computing lower bounds. Computational experience is presented to demonstrate the efficacy of this approach.