Abstract:

This work presents a hybrid multi-start algorithm for solving generic binary linear programs. This algorithm, called HMS, is based on a Multi-Start Metaheuristic and combines exact and heuristic strategies to address the problem. The initial solutions are generated by a strategy that applies linear programming and constraint propagation for defining an optimized set of fixed variables. In order to refine them, a local search, guided by a Variable Neighborhood Descent heuristic, is called, which, in turn, uses Local Branching cuts. The algorithm was tested in a set of binary LPs from the MIPLIB 2010 library and the results pointed out its competitive performance, resulting in a promising matheuristic.