New Variable Neighborhood Search Based 0-1 MIP Heuristics

Said Hanafi, Jasmina Lazić, Nenad Mladenović, Christophe Wilbaut, Igor Crevits

Abstract: In recent years many so-called matheuristics have been proposed for solving Mixed Integer Programming (MIP) problems. Though most of them are very efficient, they do not all theoretically converge to an optimal solution. In this paper we suggest two matheuristics, based on the variable neighborhood decomposition search (VNDS), and we prove their convergence. Our approach is computationally competitive with the current state-of-the-art heuristics, and on a standard benchmark of 59 0-1 MIP instances, our best heuristic achieves similar solution quality to that of a recently publishedVNDS heuristic for 0-1 MIPs within a shorter execution time.