Applications of conditional comonotonicity to some optimization problems

In this article, we study two optimization problems. The first is finding the best L1-approximant of a given random vector on some affine subspaces subject to a measurability condition. The second is finding the optimal allocation of policy limits such that the expected retained loss is minimized. Explicit solutions of both problems are constructed by utilizing the notion of conditional comonotonicity.