Open source integer linear programming solvers for error localization in numerical data

Abstract

Error localization problems can be converted into Integer Linear Programming problems. This approach provides several advantages and guarantees to find a set of erroneous fields having minimum total cost. By doing so, each erroneous record produces an Integer Linear Programming model that should be solved. This requires the use of specific solution softwares called Integer Linear Programming solvers. Some of these solvers are available as open source software. A study on the performance of internationally recognized open source Integer Linear Programming solvers, compared to a reference commercial solver on real-world data having only numerical fields, is reported. The aim was to produce a stressing test environment for selecting the most appropriate open source solver for performing error localization in numerical data.