Mic walks us through a linear optimization problem and solves it with the lpSolve package:

I’m going to implement in R an example of linear optimization that I found in the book “Modeling and Solving Linear Programming with R” by Jose M. Sallan, Oriol Lordan and Vincenc Fernandez. The example is named “Production of two models of chairs” and can be found at page 57, section 3.5. I’m going to solve only the first point.

The problem text is the following

A company produces two models of chairs: 4P and 3P. The model 4P needs 4 legs, 1 seat and 1 back. On the other hand, the model 3P needs 3 legs and 1 seat. The company has a initial stock of 200 legs, 500 seats and 100 backs. If the company needs more legs, seats and backs, it can buy standard wood blocks, whose cost is 80 euro per block. The company can produce 10 seats, 20 legs and 2 backs from a standard wood block. The cost of producing the model 4P is 30 euro/chair, meanwhile the cost of the model 3P is 40 euro/chair. Finally, the company informs that the minimum number of chairs to produce is 1000 units per month. Define a linear programming model, which minimizes the total cost (the production costs of the two chairs, plus the buying of new wood blocks).

I remember solving this exact problem (down to the four legs versus three legs bit) in grad school. We used LINGO to do this, though I haven’t seen that language since. H/T R-Bloggers