Linear Programming

These flashcards cover essential vocabulary related to linear programming and its components, allowing for effective study and understanding.

Linear Programming

A method developed by George Dantzig in the 1940s for planning problems that can be described with linear functions.

Decision Variables

Variables that represent levels of activity by a firm in a linear programming model.

Objective Function

A mathematical relationship that describes the objective of the firm in terms of decision variables, aiming to maximize or minimize its value.

Constraints

Restrictions or limitations placed on the firm by its operating environment in a linear programming model.

Feasible Solution

A solution that satisfies all of the constraints in a linear programming problem.

Infeasible Solution

A solution that violates one or more of the constraints in a linear programming problem.

Optimal Solution

A feasible solution that has the best objective value in a linear programming problem.

Slack Variable

A variable added to a 'less than or equal to' constraint to convert it into an equation, representing unused resources.

Surplus Variable

A variable subtracted from a 'greater than or equal to' constraint to convert it into an equation, representing an excess.

Graphical Analysis

A method used in linear programming to visualize constraints and solutions, particularly practical in two dimensions.