Algorithms For Dummies

  Employing Linear Programming 

     369

The model is ready to optimize (it has ingested both the objective function and the 

constraints). Call the 

solve

 method and then check its status. (Sometimes a solu-

tion may prove impossible to find or may not be optimal.)

model.solve()

print ('Completion status: %s'

       % pulp.LpStatus[model.status])

Completion status: Optimal

Having received confirmation that the optimizer found the optimal solution, you 

print the related quantities of product A and B.

print ("Production of model A = %0.1f" % A.varValue)

print ("Production of model B = %0.1f" % B.varValue)

Production of model A = 16.0

Production of model B = 6.0

In addition, you print the resulting total profit achievable by this solution.

print ('Maximum profit achieved: %0.1f'

       % pulp.value(model.objective))

Maximum profit achieved: 63000.0

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CHAPTER 20