A Parallel Meta-Solver for the Multi-Objective Set Covering Problem

The multi-objective set covering problem (MOSCP) appears in many different real-world applications. We implemented a meta-solver in C++ that introduces shared-memory concurrency using OpenMP. It incorporates a commonly used Mixed Integer Problem (MIP) solver to find initial solutions with a linear programming (LP) solver that enumerates possible solutions over a tree of subproblems using a local branch approach. Adhering to a finite cutoff value, solutions are ordered as they are passed back up the tree to produce the set of Pareto fronts. In this paper, we present a serial version of the meta-solver with a novel search procedure that outperforms a previous implementation, and when parallelization techniques are applied, a 9-12x speedup is achieved with the possibility of further improvement for large problems.