  We consider problems with multiple linear objectives and linear constraints
and use Adjustable Robust Optimization and Polynomial Optimization as tools to
approximate the Pareto set with polynomials of arbitrarily large degree. The
main difference with existing techniques is that we optimize a single
(extended) optimization problem that provides a polynomial approximation
whereas existing methods iteratively construct a piecewise linear
approximation. One of the advantages of the proposed method is that it is more
useful for visualizing the Pareto set.
