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ACCA F5 Limiting Factors Lecture 3 Example 1

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  2. dear Sir,

    thank you for another great lecture, i sometimes have trouble extending the iso contribution line and realizing which is the actual point of intersection I should use. Is its worth substituting values at both points and use the one which generates the highest contribution? in this example C or D even though it is clear here.

  5. Hi John,

    Thank you for your lectures. I am so confident doing Linear programming with 2 constraints.
    However, I have revised this topic and one of the questions gave me 3 constraints.
    1. Skilled labour hours 4x + 5y = 9600
    2. Silk Powder 3x +2y = 5000
    3. Silk Amino x + 0.5y = 1600
    Lotions demand y =2000
    Cream demand x – unlimited

    To calculate to optimum production, the solution uses 1 and 2.

    At first, I used 2 and 3. But the answer isnt the same.

    Is there any reason we should use this constraints equation rather than the others?

    This question I got from BPP Exam kit.

    Thanks,
    Angela

  6. Mr Moffat are we going to be given the value of the objective function (I.e.maximize contribution ‘C’ ) when drawing an iso-contribution line to solve for the optimal solution using the graph or we assume a value for C?

    When is it feasible to use simultaneous equations to solve for the optimum production plan not using the graph?

  7. My institute’s tutor taught this already and for some reason the way he teaches makes it hard for me to understand it but everytime i watch your lecture I understand it like magic.. Thankyou Sir Moffat! God Bless you!

  8. Wow! We can use an iso-contribution line ( a line of equal contribution) to find the optimum solution from the graph or we take the binding constraints (in this case materials and labour) to formulate another equation that can be used to find the values of S and E. This then can be used to calculate the maximum contribution. Thanks so much John for clarity in this topic.

    • Look at the graph again, its certainly not in the feasible region, another way is to put those numbers for S and E into one of the binding constraint equations.

      2S + 4E <= 80, if we were to make 24 S and 10 E, the equation would be:

      2(24) + 4(10) = 88 which is as far as I know not less than or equal to 80

  10. Hi

    Firstly, thank you so much for your excellent lectures.

    One thing I struggle with is getting a parallel outward shift of my ruler to the furthest point of production within the feasible region.

    I’m sorry if this is a silly question, but will the furthest point always coincide with the point where two of the limiting factors intersect (like it did in your example) or is it possible that the parallel outward movement of the objective function line could land on a point/corner of the feasible region before reaching the point where the two limiting factor lines intersect?

    I’m really sorry if this has not been worded clearly/is a silly question.

    Thank you.

    • The furthest point away from the origin (the optimal point) will always be where two of the constraints intersect – i.e. at one of the corners of the feasible region.
      The point of moving out the contribution line while keeping it parallel is in order to identify which of the corners is the best one.

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