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opt_without_quality_constraint.py
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opt_without_quality_constraint.py
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import random
from pulp import *
######@@@@@@@@@@--Initializations and Declarations--@@@@@@@@@@###########
#Supply limits
#s1=[random.randint(30,35), random.randint(30,35), random.randint(30,35)]
s1=random.randint(90,100)
s2=random.randint(90, 100)
s3=random.randint(90, 100)
#Demand Limits
d1=random.randint(90, 100)
d2=random.randint(90, 100)
d3=random.randint(90, 100)
#Prices of products
p1=random.randint(70,80)
p2=random.randint(35,45)
p3=random.randint(55,65)
#Cost of production and processing
c1=random.randint(50,60)
c2=random.randint(15,25)
c3=random.randint(35,45)
#quality of sources, blends and final products
a1=random.random()
a2=random.random()
a3=random.random()
b1=random.random()
b2=random.random()
b3=0
q1=random.random()
q2=random.random()
q3=random.random()
#Creating variables of flow from source to pool, with a lower limit of zero
x11=LpVariable("x11",random.randint(0,33),None,LpInteger)
x12=0
x13=LpVariable("x13",random.randint(0,33),None,LpInteger)
x21=LpVariable("x21",random.randint(0,33),None,LpInteger)
x22=0
x23=0
x31=0
x32=LpVariable("x32",random.randint(0,33),None,LpInteger)
x33=LpVariable("x33",random.randint(0,33),None,LpInteger)
#Creating variables of flow from pool to final product, with a lower limit of zero
y11=0
y12=LpVariable("y12",random.randint(0,33),None,LpInteger)
y13=0
y21=LpVariable("y21",random.randint(0,33),None,LpInteger)
y22=0
y23=LpVariable("y23",random.randint(0,33),None,LpInteger)
y31=0
y32=LpVariable("y32",random.randint(0,33),None,LpInteger)
y33=0
######@@@@@@@@@@------------------------------------@@@@@@@@@@###########
####### 1. Minimizing cost of flow from S1 ##############################
#Variable to contain problem data
prob=LpProblem("Pooling Problem", LpMinimize)
#adding objective function to prob
prob+= c1*x11+ c1*x12+ c1*x13,"flows from s1 to p1, p2 and p3"
#entering constraints to prob
prob+=x11+x12+x13 <= s1, "supply quantity from source 1 "
prob+=y11+y12+y13==x11+x21+x31,"Mass balance on pool 1"
#writing the problem in a file poolingproblem.lp
prob.writeLP("poolingproblem.lp")
#calling the solver to solve the problem
prob.solve()
#printing status
print LpStatus[prob.status]
for v in prob.variables():
print v.name,"=", v.varValue
cost1=value(prob.objective)
print "cost of flow from Source 1: ", cost1, '\n'
#######################################################################
####### 2. Minimizing cost of flow from S2 ##############################
#Variable to contain problem data
prob=LpProblem("Pooling Problem", LpMinimize)
#adding objective function to prob
prob+= c2*x21+ c2*x22+ c2*x23,"flows from s2 to p1, p2 and p3"
#entering constraints to prob
prob+=x21+x22+x23 <= s2, "supply quantity from source 2"
prob+=y21+y22+y23==x12+x22+x32,"Mass balance on pool 2"
#writing the problem in a file poolingproblem.lp
prob.writeLP("poolingproblem.lp")
#calling the solver to solve the problem
prob.solve()
#printing status
print LpStatus[prob.status]
for v in prob.variables():
print v.name,"=", v.varValue
cost2=value(prob.objective)
print "cost of flow from Source 2: ", cost2, '\n'
#######################################################################
####### 3. Minimizing cost of flow from S3 ##############################
#Variable to contain problem data
prob=LpProblem("Pooling Problem", LpMinimize)
#adding objective function to prob
prob+= c3*x31+ c3*x32+ c3*x33,"flows from s3 to p1, p2 and p3"
#entering constraints to prob
prob+=x31+x32+x33 <= s3, "supply quantity from source 3 "
prob+=y31+y32+y33==x13+x23+x33,"Mass balance on pool 3"
#writing the problem in a file poolingproblem.lp
prob.writeLP("poolingproblem.lp")
#calling the solver to solve the problem
prob.solve()
#printing status
print LpStatus[prob.status]
for v in prob.variables():
print v.name,"=", v.varValue
cost3=value(prob.objective)
print "cost of flow from Source 3: ", cost3, '\n'
#######################################################################
####### 1. Maximizing cost of flow from Pool 1 ##############################
#Variable to contain problem data
prob=LpProblem("Pooling Problem", LpMaximize)
#adding objective function to prob
prob+= p1*y11+ p1*y21+ p1*y31,"flows from pools to product 1"
#entering constraints to prob
prob+=y11+y21+y31 <= d1, "demand for product 1 "
#writing the problem in a file poolingproblem.lp
prob.writeLP("poolingproblem.lp")
#calling the solver to solve the problem
prob.solve()
#printing status
print LpStatus[prob.status]
for v in prob.variables():
print v.name,"=", v.varValue
sp1=value(prob.objective)
print "selling price of product 1: ", sp1,'\n'
#######################################################################
####### 2. Maximizing cost of flow from Pool 2 ##############################
#Variable to contain problem data
prob=LpProblem("Pooling Problem", LpMaximize)
#adding objective function to prob
prob+= p2*y12+ p2*y22+ p2*y32,"flows from pools to product 2 "
#entering constraints to prob
prob+=y12+y22+y32 <= d2, "demand for product 2 "
#writing the problem in a file poolingproblem.lp
prob.writeLP("poolingproblem.lp")
#calling the solver to solve the problem
prob.solve()
#printing status
print LpStatus[prob.status]
for v in prob.variables():
print v.name,"=", v.varValue
sp2=value(prob.objective)
print "selling price of product 2: ", sp2, '\n'
#######################################################################
####### 3. Maximizing cost of flow from Pool 3 ##############################
#Variable to contain problem data
prob=LpProblem("Pooling Problem", LpMaximize)
#adding objective function to prob
prob+= p3*y13+ p3*y23+ p3*y33,"flows from pools to product 3"
#entering constraints to prob
prob+=y13+y23+y33 <= d3, "demand for product 3 "
#writing the problem in a file poolingproblem.lp
prob.writeLP("poolingproblem.lp")
#calling the solver to solve the problem
prob.solve()
#printing status
print LpStatus[prob.status]
for v in prob.variables():
print v.name,"=", v.varValue
sp3=value(prob.objective)
print "selling price of product 3: ", sp3, '\n'
#######################################################################
print "\nFinal Maximized profit : ", (sp1-cost1)+(sp2-cost2)+(sp3-cost3)