Safety-First Rules under Chance-Constrained Linear Programming

Abstract

The approach of chance-constrained linear programming is analyzed here in the context of safety-first principles based on Tchebycheff-type inequalities. The analysis attempts to define relatively distribution-free tolerance levels and the incidence of nonnormality in chance-constrained linear programming.