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We explore two less conventional applications of multi-objective linear programming (MOLP).

In the first application, we employ a MOLP solver to compute geometric operations on polyhedra, including the Minkowski sum, intersection, and the convex hull of their union.

The second application addresses multi-objective optimization problems involving two sequential decision makers. The first decision maker controls a subset of variables and acts initially, while the second controls the remaining variables and acts subsequently. This setting gives rise to a multi-stage decision problem, which can be interpreted as an optimization problem with a set-valued objective function — commonly referred to as a set optimization problem. We examine this framework in detail, discussing solution methodologies, the underlying decision-making structure, and practical applications. Furthermore, we highlight the equivalence of such problems to classical multi-objective linear programs.