Jip J. Dekker
f2a1c4e389
git-subtree-dir: software/mza git-subtree-split: f970a59b177c13ca3dd8aaef8cc6681d83b7e813
54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
# A political problem
|
|
|
|
# Suppose that you are a politician trying to win an election. Your district has three
|
|
# different types of areas - urban, suburban, and rural. These areas have, respectively,
|
|
# 100,000, 200,000, and 50,000 registered voters. Although not all the registered voters
|
|
# actually go to the polls, you decide that to govern effectively, you would like at least
|
|
# half the registered voters in each of the three regions to vote for you. You are honorable
|
|
# and would never consider supporting policies in which you do not believe. You realize,
|
|
# however, that certain issues may be more effective in winning votes in certain places.
|
|
# Your primary issues are building more roads, gun control, farm subsidies, and a gasoline tax
|
|
# dedicated to improved public transit.
|
|
# According to your campaign staff's research, you can estimate how many votes you win or lose
|
|
# from each population segment by spending $1,000 on advertising on each issue.
|
|
# POLICY | URBAN SUBURBAN RURAL
|
|
# -----------------------------------------
|
|
# build roads | -2 5 3
|
|
# gun control | 8 2 -5
|
|
# farm subsidies | 0 0 10
|
|
# gasoline tax | 10 0 -2
|
|
#
|
|
# In this table, each entry indicates the number of thousands of either urban, suburban,
|
|
# or rural voters who would be won over by spending $1,000 on advertising in support of
|
|
# a particular issue. Negative entries denote votes that would be lost.
|
|
# Your task is to figure out the minimum amount of mony that you need to spend in order to win
|
|
# 50,000 urban votes, 10,000 suburban votes, and 25,000 rural votes.
|
|
|
|
|
|
from minizinc import *
|
|
|
|
m = Model()
|
|
|
|
x1 = m.Variable(0.0,10000.0)
|
|
x2 = m.Variable(0.0,10000.0)
|
|
x3 = m.Variable(0.0,10000.0)
|
|
x4 = m.Variable(0.0,10000.0)
|
|
|
|
m.Constraint( -2.0*x1 + 8.0*x2 + 0.0*x3 + 10.0*x4 >= 50.0,
|
|
5.0*x1 + 2.0*x2 + 0.0*x3 + 0.0*x4 >= 100.0,
|
|
3.0*x1 - 5.0*x2 + 10.0*x3 - 2.0*x4 >= 25.0,
|
|
)
|
|
|
|
m._debugprint()
|
|
m.mznmodel.set_time_limit(10)
|
|
|
|
m.minimize(x1+x2+x3+x4)
|
|
|
|
m.next()
|
|
|
|
print "Minimize cost = ", x1 + x2 + x3 + x4
|
|
print "where x1 = ", x1
|
|
print " x2 = ", x2
|
|
print " x3 = ", x3
|
|
print " x4 = ", x4
|