Explore a realistic approach to linear programming with random coefficients and risk analysis. Discover how to design a copula of objective function coefficients for business analytics and risk ...

Discover how fuzzy programming methods, such as Chandra Sen's and statistical averaging, can convert multi-objective linear programming problems into single objective functions. Explore numerical and ...

Linear programming is a mathematical method for optimizing a linear function, called the objective function, subject to a set of linear constraints. For example, you might want to maximize your ...

Learn how to create a linear programming problem from scratch, using a simple and systematic approach. Find out how to identify the variables, define the objective function, formulate the ...

Bilevel linear programming (BLP) is a solution method for linear optimization problem with two sequential decision steps of the leader and the follower. In this paper, we assume that the follower's ...

In this paper, we present a new method to solve a fuzzy linear programming problem with fuzzy coefficients in the constraints and the objective function based on solving an associated multi-objective ...

In linear programming, the objective function is the function that it is desired to maximize or minimize. The human interaction equivalent is what matters most.

The SimplexMethod package provides an efficient implementation of the Simplex Algorithm for solving linear programming (LP) problems. It supports both maximization and minimization of objective ...

In this paper we propose a stochastic programming model which considers the distribution of an objective function and probabilistic constraints. Applying it to a transportation type problem, we derive ...