The traditional linear programming model is deterministic. The way that uncertainty is handled is to compute the range of optimality. After the optimal solution is obtained, typically by the simplex ...

Linear and nonlinear programming are two types of optimization methods that can help you find the best solution to a problem involving decision variables, constraints, and an objective function.

Linear programming is appropriate for this problem as the constraints and objective function are linear in form (i.e. They can be expressed as linear combinations of decision variables and ...

Utilize the weighted average method or the lexicographic method to find a Pareto optimal solution for the given bi-objective linear program. Modified Objective Functions: In a revised version of the ...

Abstract: In this paper, we focus on two-level linear programming problems involving random variable coefficients in objective functions and/or constraints. Using chance constrained programming ...

In this paper, we study the fuzzy bilevel programming problem in which the coefficients in the objective functions and the constraints are assumed to be fuzzy numbers. In comparison with deterministic ...

Solving linear programming problems in a spreadsheet yields equations for maximizing business profits. As applied to business, linear programming typically involves an objective formula, such as ...

The purpose of this paper is to present a Monte Carlo solution for a random objective function coefficient linear programming problem that can be executed in Excel. A solution was given in Ridley and ...