Journal Article
In this paper, the authors consider generating a representative subset of nondominated points at a prespecified precision in multi-objective mixed-integer programs (MOMIPs)
The number of nondominated points grows exponentially with problem size and finding all nondominated points is typically hard in MOMIPs. Representing the nondominated set with a small subset of nondominated points is important for a decision maker to get an understanding of the layout of solutions. The shape and density of the nondominated points over the objective space may be critical in obtaining a set of solutions that represent the nondominated set well.
The authors develop an exact algorithm that generates a representative set guaranteeing a prespecified precision. The authors' experiments on a variety of problems demonstrate that their algorithm outperforms existing approaches in terms of both the cardinality of the representative set and computation times.
