Linear programming
Linear programming optimises a linear objective subject to linear constraints and non-negativity or other stated restrictions. Define decision variables, express contribution or cost as the objective, and translate each resource or demand condition into the correct inequality. A graphical method is useful for two decision variables; software can solve larger models. Interpret the feasible solution, binding constraints and shadow prices rather than assuming a numerical optimum is operationally certain.
Worked example
Maximise 8x + 10y subject to 2x + y ≤ 100 and x + 3y ≤ 120, with x and y non-negative. Each expression must use consistent resource units.
Common mistake
A product ranking by one resource is not generally valid when several resource constraints interact.
Where it appears in your exams
| Qualification | Exam | Relationship | Period |
|---|---|---|---|
| ACCA | PM | Direct | September 2026–June 2027 |