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"""
The Furniture problem from EngSci391 for the PuLP Modeller
Author: Dr Stuart Mitchell 2007
"""
from pulp import *
Chairs = ["A", "B"]
costs = {"A": 100, "B": 150}
Resources = ["Lathe", "Polisher"]
capacity = {"Lathe": 40, "Polisher": 48}
activity = [ # Chairs
# A B
[1, 2], # Lathe
[3, 1.5], # Polisher
]
activity = makeDict([Resources, Chairs], activity)
prob = LpProblem("Furniture Manufacturing Problem", LpMaximize)
vars = LpVariable.dicts("Number of Chairs", Chairs, lowBound=0)
# objective
prob += lpSum([costs[c] * vars[c] for c in Chairs])
for r in Resources:
prob += (
lpSum([activity[r][c] * vars[c] for c in Chairs]) <= capacity[r],
"capacity_of_%s" % r,
)
prob.writeLP("furniture.lp")
prob.solve()
# Each of the variables is printed with it's value
for v in prob.variables():
print(v.name, "=", v.varValue)
# The optimised objective function value is printed to the screen
print("Total Revenue from Production = ", value(prob.objective))
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