how does linear programing helps to increase capacity utilization?

Answer 1

Linear programming helps because it combines the constraints of several resources and allows you to solve for optimal solution given your parameters.

So, in a small factory, you might know that each builder can build 2 widgets per hour.

But the painter can paint 4 widgets an hour.

You might have 2 builders and 2 painters. Clearly, there is capacity that's being underutilized (1 painter).

Using LP, you could put the two processes together in a formula and see that as you increase the number of builders, that you can still keep the painters constant and still increase capacity.

Right now, you produce 4 widgets per hour with 4 employees. Your actual productivity is 1 employee hour per widget. If you add two builders, you now have doubled your capacity while increasing your employees only 50% because you're cranking out 8 widgets an hour with only 6 employees. Not bad!

Likewise, you can adjust several other parameters to find answers to other questions as well.

But for your question, this is how LP helps!

Answer 2

Linear Programming allows you to minimize or maximize one characteristic of a model while constraining others.

For example, I used it to choose bond portfolios. My objective was to minimize costs and the constraints were to make sure there was always money on hand to make liability payments, make sure that no more than five percent of the portfolio was invested in any one company, make sure that no more than 20% of the portfolio was invested in any one sector, constrain how much could be invested in wea kcredits, etc.

You could do the same thing with capacity utilization -- maximize it subject to certain constraints on time, resources and suply of other inputs.

The following link might help.