Stackelberg Solutions to Two-Level Linear Programming Problems with Random Variable Coefficients

In this paper, to cope with hierarchical decision making problems under uncertainty, we formulate a two-level linear programming problem in which random variable coefficients are involved in objective functions and constraints, and reduce the problem into deterministic problems by using two models. While one of the deterministic problems is a usual two-level linear programming problem, the other is a two-level quadratic one. We present a computational method for obtaining Stackelberg solutions to the reduced deterministic two-level quadratic programming problems.