| Binding constraint | A constraint that forms the optimal corner point of the feasible solution space.
|
 |
|
|
| Constraints | Limitations that restrict the available alternatives.
|
|
|
|
| Decision variables | Amounts of either inputs or outputs.
|
|
|
|
| Enumeration approach | Substituting the coordinates of each corner point into the objective function to determine which corner point is optimal.
|
|
|
|
| Feasible solution space | The set of all feasible combinations of decision variables as defined by the constraints.
|
|
|
|
| Graphical linear programming | Graphical method for finding optimal solutions to twovariable problems.
|
|
|
|
| Objective function | Mathematical statement of profit (or cost, etc.) for a given solution.
|
|
|
|
| Parameters | Numerical constants.
|
|
|
|
| Range of feasibility | Range of values for the RHS of a constraint over which the shadow price remains the same.
|
|
|
|
| Range of optimality | Range of values over which the solution quantities of all the decision variables remain the same.
|
|
|
|
| Redundant constraint | A constraint that does not form a unique boundary of the feasible solution space.
|
|
|
|
| Sensitivity analysis | Assessing the impact of potential changes to the numerical values of an LP model.
|
|
|
|
| Shadow price | Amount by which the value of the objective function would change with a one-unit change in the RHS value of a constraint.
|
|
|
|
| Simplex | A linear programming algorithm that can solve problems having more than two decision variables.
|
|
|
|
| Slack | When the values of decision variables are substituted into a ≤ constraint the amount by which the resulting value is less than the right-hand-side value.
|
|
|
|
| Surplus | When the values of decision variables are substituted into a ≥ constraint the amount by which the resulting value exceeds the right-hand-side value.
|