Technical Note—A Class of Nonlinear Chance-Constrained Programming Models with Joint Constraints

Abstract

Miller and Wagner [ Opns. Res. 13, 930–945 (1965)] define joint chance-constrained programming by specifying a set of constants that are joint probability measures of the extent to which constraint violations are permitted. For the special case of a random right-hand-side vector whose elements are independent random variables, they show that an equivalent deterministic concave program exists. The purpose of this paper is to generalize this result to a class of nonlinear chance-constrained programming models with joint constraints.