Heuristic approaches to the Distinguishing Substring Selection Problem

The Distinguishing Substring Selection Problem aims to find a target string close to all strings in a given set of good strings and far enough of strings in another set of bad strings. This problem has applications in bioinformatics and it is related to the closest substring problem and other string selection problems. In this work, we investigate two heuristics for the problem based on rounding procedures and variable neighborhood search approaches. Both heuristics consider the solution of the linear relaxation of an integer programming formulation for the problem as an initial solution. We conducted computational experiments in three groups of instances. The rounding procedure provides good solutions and the VNS improves these results using different rounding procedures as neighborhood structures. To the best of our knowledge, this is the first paper that provides computational results for the problem.