ILP Models and Column Generation for the Minimum Sum Coloring Problem

Abstract We study two Integer Linear Programming (ILP) formulations for the Minimum Sum Coloring Problem (MSCP). The problem is an extension of the classical Vertex Coloring Problem in which each color is represented by a positive natural number. The MSCP asks to minimize the sum of the cardinality of subsets of vertices receiving the same color, weighted by the index of the color, while ensuring that vertices linked by an edge receive different colors. The first ILP formulation has a polynomial number of variables while the second one has an exponential number of variables and is tackled via column generation. Computational tests show that the linear programming relaxation of the second formulation provides tight lower bounds which allow us to solve to proven optimality some hard instances of the literature.