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