Final Exam Flashcards
The expression that defines the quantity to be maximized or minimized in a linear programming model.
Objective Function
Restrictions that limit the settings of the decision variables.
Constraints
The process of translating a verbal statement of a problem into a mathematical statement called the mathematical model.
Problem Formation
A controllable input for a linear programming model.
Decision Variables
A set of constraints that requires all variables to be nonnegative.
Non-negativity constraints
A mathematical function in which each variable appears in a separate term and is raised to the first power.
Linear Function (LP Simplex)
A solution that satisfies all the constraints simultaneously.
Feasible Solution
The situation in which no solution to the linear programming problem satisfies all the constraints.
Infeasible Solution
Graphically speaking, the feasible solution points occurring at the vertices, or “corners,” of the feasible region. With two-variable problems, extreme points are determined by the intersection of the constraint lines.
Extreme Points
The set of all feasible solutions.
Feasible Region
The difference between the right-hand-side and the left-hand-side of a less-than-or-equal-to constraint.
Slack
A constraint that holds as an equality at the optimal solution.
Binding
A variable subtracted from the left-hand side of a greater-than-or-equal-to constraint to convert the constraint into an equality. The value of this variable can usually be interpreted as the amount over and above some required minimum level.
Surplus
The situation in which the value of the solution may be made infinitely large in a maximization linear programming problem or infinitely small in a minimization problem without violating any of the constraints.
Unbounded
A controllable input for a linear programming model.
Decision Variable
