Chance Constrained Programming with Joint Constraints

摘要: This paper considers the mathematical properties of chance constrained programming problems where restriction is on joint probability a multivariate random event. One model that considered arises when right-handside constants linear constraints are random. Another treated here occurs coefficients variables described by multinormal distribution. It shown under certain restrictions both situations can be viewed as deterministic nonlinear problem. Since most computational methods for solving models require concave, this explores whether resultant problem meets concavity assumption. For many laws practical importance, constraint in first type to violate concavity. However, simple logarithmic transformation does produce concave an important class problems. The also surveys "generalized programming" method such justified. second model, demonstrated nonconcave.