Big-M Method (Edexcel A-Level Further Mathematics): Revision Notes
📚 Revision Notes
12.3.3 Big-M Method
Introduction
The Big-M method is an alternative to the two-stage Simplex method for solving problems with or equality constraints. It introduces artificial variables and assigns them a very large penalty () in the objective function to ensure they are removed from the solution.
The Role of
Artificial variables are penalised in the objective function to discourage their inclusion in the final solution:
- For maximisation: is added with a negative coefficient.
- For minimisation: is added with a positive coefficient.
Process
- Formulate the problem by adding slack, surplus, and artificial variables.
- Modify the objective function to include terms for artificial variables.
- Solve the problem using the Simplex method.
Worked Example
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Problem
Maximise:
Subject to:
Step 1: Add Variables
- Add a slack variable for
- Add a surplus variable and an artificial variable for
Step 2: Modify the Objective Function
Add -M for the artificial variable :
Step 3: Set Up Initial Tableau
Step 4: Solve Using Simplex
Apply the Simplex algorithm to:
- Remove artificial variables ()
- Maximise by optimising the remaining variables.
Note Summary
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Common Mistakes
- Incorrect -term signs: Using +M for maximisation or -M for minimisation.
- Forgetting surplus variables: Omitting surplus variables in constraints.
- Artificial variable errors: Not penalising artificial variables in the objective function.
- Arithmetic errors: Mistakes during pivoting steps.
- Ignoring non-negativity: Forgetting
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Key Formulas
- Objective function with :
- Slack and surplus variables:
- Feasibility check: Artificial variables must exit the basis to achieve an optimal solution.