def solve(filename, method):
s = CyClpSimplex()
s.readMps(filename)
s.preSolve(feasibilityTolerance=10 ** -8)
#s.useCustomPrimal(1)
if method == 'd':
pivot = DantzigPivot(s)
elif method == 'l':
pivot = LIFOPivot(s)
elif method == 'm':
pivot = MostFrequentPivot(s)
elif method == 'p':
pivot = PositiveEdgePivot(s)
else:
print('Unkown solution method.')
sys.exit(1)
s.setPivotMethod(pivot)
#s.setPerturbation(50)
start = clock()
s.primal()
print('Problem solved in %g seconds.' % (clock() - start))
return s.objectiveValue
def solve(filename, method):
s = CyClpSimplex()
s.readMps(filename)
s.preSolve(feasibilityTolerance=10 ** -8)
#s.useCustomPrimal(1)
if method == 'd':
pivot = DantzigPivot(s)
elif method == 'l':
pivot = LIFOPivot(s)
elif method == 'm':
pivot = MostFrequentPivot(s)
elif method == 'p':
pivot = PositiveEdgePivot(s)
else:
print 'Unkown solution method.'
sys.exit(1)
s.setPivotMethod(pivot)
#s.setPerturbation(50)
start = clock()
s.primal()
print 'Problem solved in %g seconds.' % (clock() - start)
return s.objectiveValue
def test_1(self):
"""simplest QP test"""
s = CyClpSimplex()
s.readMps(join(currentFilePath, '../input/hs35.qps'))
#self.assertTrue(abs(cbcModel.objectiveValue - 3089.0) < 10 ** -6)
#print s.Hessian.todense()
p = WolfePivot(s)
s.setPivotMethod(p)
s.primal()
print s.primalVariableSolution
print s.objectiveValue
def test_1(self):
"""simplest QP test"""
s = CyClpSimplex()
s.readMps(join(currentFilePath, '../input/hs35.qps'))
#self.assertTrue(abs(cbcModel.objectiveValue - 3089.0) < 10 ** -6)
#print s.Hessian.todense()
p = WolfePivot(s)
s.setPivotMethod(p)
s.primal()
print s.primalVariableSolution
print s.objectiveValue
class TestCyClpSimplex(unittest.TestCase):
def setUp(self):
self.s = CyClpSimplex()
self.s.readMps(join(currentFilePath, '../input/p0033.mps'))
def test_PE(self):
#pivot = PositiveEdgePivot(self.s)
self.s.setPivotMethod(PositiveEdgePivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_Dantzig(self):
#pivot = DantzigPivot(self.s)
self.s.setPivotMethod(DantzigPivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_LIFO(self):
#pivot = LIFOPivot(self.s)
self.s.setPivotMethod(LIFOPivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_MostFrequent(self):
#pivot = MostFrequentPivot(self.s)
self.s.setPivotMethod(MostFrequentPivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_initialSolve(self):
self.s.initialSolve()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_initialPrimalSolve(self):
self.s.initialPrimalSolve()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_initialDualSolve(self):
self.s.initialDualSolve()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_direction(self):
self.assertEqual(self.s.optimizationDirection, 'min')
self.s.optimizationDirection = 'max'
self.assertEqual(self.s.optimizationDirection, 'max')
class TestCyClpSimplex(unittest.TestCase):
def setUp(self):
self.s = CyClpSimplex()
self.s.readMps(join(currentFilePath, '../input/p0033.mps'))
def test_PE(self):
#pivot = PositiveEdgePivot(self.s)
self.s.setPivotMethod(PositiveEdgePivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_Dantzig(self):
#pivot = DantzigPivot(self.s)
self.s.setPivotMethod(DantzigPivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_LIFO(self):
#pivot = LIFOPivot(self.s)
self.s.setPivotMethod(LIFOPivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_MostFrequent(self):
#pivot = MostFrequentPivot(self.s)
self.s.setPivotMethod(MostFrequentPivot(self.s))
self.s.primal()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_initialSolve(self):
self.s.initialSolve()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_initialPrimalSolve(self):
self.s.initialPrimalSolve()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_initialDualSolve(self):
self.s.initialDualSolve()
self.assertEqual(round(self.s.objectiveValue, 4), 2520.5717)
def test_direction(self):
self.assertEqual(self.s.optimizationDirection, 'min')
self.s.optimizationDirection = 'max'
self.assertEqual(self.s.optimizationDirection, 'max')
def test_NodeCompare(self):
s = CyClpSimplex()
s.readMps(join(currentFilePath, '../input/p0033.mps'))
s.copyInIntegerInformation(np.array(s.nCols * [True], np.uint8))
print("Solving relaxation")
cbcModel = s.getCbcModel()
n = SimpleNodeCompare()
cbcModel.setNodeCompare(n)
gom = CyCglGomory(limit=150)
#gom.limit = 150
cbcModel.addCutGenerator(gom, name="Gomory")
#clq = CyCglClique()
#cbcModel.addCutGenerator(clq, name="Clique")
knap = CyCglKnapsackCover(maxInKnapsack=50)
cbcModel.addCutGenerator(knap, name="Knapsack")
cbcModel.branchAndBound()
self.assertTrue(abs(cbcModel.objectiveValue - 3089.0) < 10**-6)
def test_NodeCompare(self):
s = CyClpSimplex()
s.readMps(join(currentFilePath, '../input/p0033.mps'))
s.copyInIntegerInformation(np.array(s.nCols * [True], np.uint8))
print "Solving relaxation"
cbcModel = s.getCbcModel()
n = SimpleNodeCompare()
cbcModel.setNodeCompare(n)
gom = CyCglGomory(limit=150)
#gom.limit = 150
cbcModel.addCutGenerator(gom, name="Gomory")
#clq = CyCglClique()
#cbcModel.addCutGenerator(clq, name="Clique")
knap = CyCglKnapsackCover(maxInKnapsack=50)
cbcModel.addCutGenerator(knap, name="Knapsack")
cbcModel.branchAndBound()
self.assertTrue(abs(cbcModel.objectiveValue - 3089.0) < 10 ** -6)
#del rc2
return indicesToConsider[ind]
return -1
def saveWeights(self, model, mode):
self.clpModel = model
def isPivotAcceptable(self):
return True
def getMpsExample():
import os
import inspect
cylpDir = os.environ['CYLP_SOURCE_DIR']
return os.path.join(cylpDir, 'cylp', 'input', 'p0033.mps')
if __name__ == "__main__":
if len(sys.argv) == 1:
import doctest
doctest.testmod()
else:
from cylp.cy import CyClpSimplex
from cylp.py.pivots import DantzigPivot
s = CyClpSimplex()
s.readMps(sys.argv[1])
pivot = DantzigPivot(s)
s.setPivotMethod(pivot)
s.primal()
#del rc2
return indicesToConsider[ind]
return -1
def saveWeights(self, model, mode):
self.clpModel = model
def isPivotAcceptable(self):
return True
def getMpsExample():
import os
import inspect
cylpDir = os.environ['CYLP_SOURCE_DIR']
return os.path.join(cylpDir, 'cylp', 'input', 'p0033.mps')
if __name__ == "__main__":
if len(sys.argv) == 1:
import doctest
doctest.testmod()
else:
from cylp.cy import CyClpSimplex
from cylp.py.pivots import DantzigPivot
s = CyClpSimplex()
s.readMps(sys.argv[1])
pivot = DantzigPivot(s)
s.setPivotMethod(pivot)
s.primal()
model.solution[basicVarInds[rowNumbers]] -= change
changeObj = -np.dot(change, cost)
primalUpdate.clear()
objectiveChange[0] += changeObj
return changeObj
def getMpsExample():
import os
import inspect
import sys
cylpDir = os.environ['CYLP_SOURCE_DIR']
return os.path.join(cylpDir, 'cylp', 'input', 'p0033.mps')
if __name__ == "__main__":
print(sys.argv)
if len(sys.argv) == 1:
import doctest
doctest.testmod()
else:
from cylp.cy import CyClpSimplex
from cylp.py.pivots import DualDantzigPivot
s = CyClpSimplex()
s.readMps(sys.argv[1]) # Returns 0 if OK
pivot = DualDantzigPivot(s)
s.setDualPivotMethod(pivot)
s.dual()
if __name__ == "__main__":
mip_model = MIPModel(GurobiSolver())
starttime1 = timeit.default_timer()
load_mps_primitive(mip_model, path="../../examples/mps_files/10teams.mps")
endtime1 = timeit.default_timer()
mip_model.set_mip_sense(LPSense.MIN)
starttime2 = timeit.default_timer()
mip_model.lp_model.optimize()
endtime2 = timeit.default_timer()
first_value = mip_model.lp_model.get_objective_value()
mip_model = MIPModel(GurobiSolver())
starttime3 = timeit.default_timer()
load_mps_advanced(mip_model, path="../../examples/mps_files/10teams.mps")
endtime3 = timeit.default_timer()
mip_model.set_mip_sense(LPSense.MIN)
starttime4 = timeit.default_timer()
mip_model.lp_model.optimize()
endtime4 = timeit.default_timer()
second_value = mip_model.lp_model.get_objective_value()
print(
"Primitive Load: {}s loading time, {}s optimization time, objective value: {}\nAdvanced Load: {}s loading time, {}s optimization time, objective value: {}"
.format(endtime1 - starttime1, endtime2 - starttime2, first_value,
endtime3 - starttime3, endtime4 - starttime4, second_value))
from cylp.cy import CyClpSimplex
s = CyClpSimplex()
s.readMps("../../examples/mps_files/10teams.mps")
s.initialSolve()
print(s.objectiveValue)
print(s.solution)
model.solution[basicVarInds[rowNumbers]] -= change
changeObj = -np.dot(change, cost)
primalUpdate.clear()
objectiveChange[0] += changeObj
return changeObj
def getMpsExample():
import os
import inspect
import sys
cylpDir = os.environ['CYLP_SOURCE_DIR']
return os.path.join(cylpDir, 'cylp', 'input', 'p0033.mps')
if __name__ == "__main__":
print sys.argv
if len(sys.argv) == 1:
import doctest
doctest.testmod()
else:
from cylp.cy import CyClpSimplex
from cylp.py.pivots import DualDantzigPivot
s = CyClpSimplex()
s.readMps(sys.argv[1]) # Returns 0 if OK
pivot = DualDantzigPivot(s)
s.setDualPivotMethod(pivot)
s.dual()
#!/usr/bin/env python3
import numpy as np
from cylp.cy import CyClpSimplex
from cylp.py.modeling.CyLPModel import CyLPArray
s = CyClpSimplex()
s.readMps("/Users/cassie/Dropbox/GA/Website/example.lp")
s.initialSolve()
# # Add variables
# x = s.addVariable('x', 3)
# y = s.addVariable('y', 2)
# # Create coefficients and bounds
# A = np.matrix([[1., 2., 0],[1., 0, 1.]])
# B = np.matrix([[1., 0, 0], [0, 0, 1.]])
# D = np.matrix([[1., 2.],[0, 1]])
# a = CyLPArray([5, 2.5])
# b = CyLPArray([4.2, 3])
# x_u= CyLPArray([2., 3.5])
# # Add constraints
# s += A * x <= a
# s += 2 <= B * x + D * y <= b
# s += y >= 0
# s += 1.1 <= x[1:3] <= x_u
# # Set the objective function
# c = CyLPArray([1., -2., 3.])
