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Lesson 93

Graphical linear programming - part 2

Graphical linear programming enables you to visually identify the optimal production mix that maximises contribution when facing multiple constraints. This lesson demonstrates how to construct constraint lines, define feasible regions, and apply objective functions to determine the profit-maximising output levels for two products by combining labour and materials limitations with mathematical optimisation techniques.

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In this lesson

  1. 0:00 Introduction to Linear Programming
  2. 0:41 Understanding Objective Function
  3. 1:06 Exploring Labour Constraint
  4. 1:10 Direct Materials Constraint
  5. 1:39 Identifying Optimal Solution
  6. 2:01 Feasible Region Explained
  7. 2:40 Mathematical Example Begins
  8. 3:50 Calculating Maximum Contribution
  9. 5:38 Optimal Solution Revealed

About this lesson

Discover the intricacies of graphical linear programming in part 2 of our series, where we delve into optimising production for maximum contribution. This video walks you through a visual and mathematical example, highlighting objective functions, constraint lines, and feasible regions, to find the optimal solution for producing two products, X and Y. Understand how to apply constraints in labour and materials to maximise output efficiently. Perfect for business professionals seeking actionable insights on optimising production processes, this tutorial offers a clear path to mastering linear programming.

Duration: 6m

  • Objective function formulation
  • Constraint line plotting
  • Feasible region identification
  • Labour and materials constraints
  • Optimal solution determination
  • Contribution maximisation

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