A cutting plane approach for chance constrained linear programs

One approach for solving linear programs with random coefficients is chance constrained programming. For the case where the technical coefficients are normally distributed, the authors present a convergent cutting plane algorithm to solve the equivalent nonlinear program, which takes advantage of the characteristics of the problem. The algorithm requires a moderate computational effort and compares favorably with a general nonlinear code and other approaches proposed for solving this problem.