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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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