Multi-objective optimization with convex quadratic cost functions: A multi-parametric programming approach

•Formulation of the multi-objective optimization problem as a multi-parametric QCQP.•Derivation of suitable affine overestimators with a guaranteed bound of suboptimality.•Solution of the resulting mp-QP problem with state-of-the-art solvers, thus obtaining the Pareto front explicitly.•Numerical examples highlight the capabilities of this approach.

In this note we present an approximate algorithm for the explicit calculation of the Pareto front for multi-objective optimization problems featuring convex quadratic cost functions and linear constraints based on multi-parametric programming and employing a set of suitable overestimators with tunable suboptimality. A numerical example as well as a small computational study highlight the features of the novel algorithm.