Chance-Constrained Critical Path for a Large Class of Distributions

摘要

M. Kress proved for a special class of Location-Scale probability distributions there always exists a probability level for which the Chance Constrained Critical Path (CCCP) remains unchanged for all probabilities greater than or equal to that value. His chance constrained problem has zero-order decision rules and individual chance constraints. This paper extends his results to most of the common probability distributions. Keywords: Chance constrained programming. (KR)