The MIN PFS problem and piecewise linear model estimation
Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
On Exact Selection of Minimally Unsatisfiable Subformulae
Annals of Mathematics and Artificial Intelligence
Computing customized page ranks
ACM Transactions on Internet Technology (TOIT)
Solution techniques for the Large Set Covering Problem
Discrete Applied Mathematics
Boundedness Theorems for the Relaxation Method
Mathematics of Operations Research
Repairing MIP infeasibility through local branching
Computers and Operations Research
A two-phase relaxation-based heuristic for the maximum feasible subsystem problem
Computers and Operations Research
Heuristic algorithms in computational molecular biology
Journal of Computer and System Sciences
A relaxable service selection algorithm for QoS-based web service composition
Information and Software Technology
Randomized relaxation methods for the maximum feasible subsystem problem
IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Integrated classifier hyperplane placement and feature selection
Expert Systems with Applications: An International Journal
Approximating infeasible 2VPI-systems
WG'12 Proceedings of the 38th international conference on Graph-Theoretic Concepts in Computer Science
Adaptive scheduling for parallel tasks with QoS satisfaction for hybrid cloud environments
The Journal of Supercomputing
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Given an infeasible set of linear constraints, finding the maximum cardinality feasible subsystem is known as themaximum feasible subsystem problem. This problem is known to be NP-hard, but has many practical applications. This paper presents improved heuristics for solving the maximum feasible subsystem problem that are significantly faster than the original, but still highly accurate.