  A risk-aware decision-making problem can be formulated as a
chance-constrained linear program in probability measure space.
Chance-constrained linear program in probability measure space is intractable,
and no numerical method exists to solve this problem. This paper presents
numerical methods to solve chance-constrained linear programs in probability
measure space for the first time. We propose two solvable optimization problems
as approximate problems of the original problem. We prove the uniform
convergence of each approximate problem. Moreover, numerical experiments have
been implemented to validate the proposed methods.
