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fix #911, rewrite example to use CP-SAT

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Laurent Perron
2018-11-06 08:44:56 +01:00
parent fd7c91abc2
commit 77ffc2abb2
1 changed files with 22 additions and 31 deletions
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53
examples/python/diet1.py
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@@ -44,12 +44,12 @@
http://www.hakank.org/google_or_tools/
"""
from __future__ import print_function
from ortools.constraint_solver import pywrapcp
from ortools.sat.python import cp_model
def main(unused_argv):
# Create the solver.
solver = pywrapcp.Solver("Diet")
model = cp_model.CpModel()
#
# data
@@ -67,43 +67,34 @@ def main(unused_argv):
#
# declare variables
#
x = [solver.IntVar(0, 100, "x%d" % i) for i in range(n)]
cost = solver.IntVar(0, 10000, "cost")
x = [model.NewIntVar(0, 100, "x%d" % i) for i in range(n)]
cost = model.NewIntVar(0, 10000, "cost")
#
# constraints
#
solver.Add(solver.Sum([x[i] * calories[i] for i in range(n)]) >= limits[0])
solver.Add(solver.Sum([x[i] * chocolate[i] for i in range(n)]) >= limits[1])
solver.Add(solver.Sum([x[i] * sugar[i] for i in range(n)]) >= limits[2])
solver.Add(solver.Sum([x[i] * fat[i] for i in range(n)]) >= limits[3])
model.Add(sum(x[i] * calories[i] for i in range(n)) >= limits[0])
model.Add(sum(x[i] * chocolate[i] for i in range(n)) >= limits[1])
model.Add(sum(x[i] * sugar[i] for i in range(n)) >= limits[2])
model.Add(sum(x[i] * fat[i] for i in range(n)) >= limits[3])
# objective
objective = solver.Minimize(cost, 1)
model.Minimize(cost)
#
# solution
#
solution = solver.Assignment()
solution.AddObjective(cost)
solution.Add(x)
# Solve model.
solver = cp_model.CpSolver()
status = solver.Solve(model)
# last solution since it's a minimization problem
collector = solver.LastSolutionCollector(solution)
search_log = solver.SearchLog(100, cost)
solver.Solve(
solver.Phase(x + [cost], solver.INT_VAR_SIMPLE, solver.ASSIGN_MIN_VALUE),
[objective, search_log, collector])
# get the first (and only) solution
print("cost:", collector.ObjectiveValue(0))
print([("abcdefghij" [i], collector.Value(0, x[i])) for i in range(n)])
print()
print("failures:", solver.Failures())
print("branches:", solver.Branches())
print("WallTime:", solver.WallTime())
print()
# Output solution.
if status == cp_model.OPTIMAL:
print("cost:", solver.ObjectiveValue())
print([("abcdefghij" [i], solver.Value(x[i])) for i in range(n)])
print()
print(' - status : %s' % solver.StatusName(status))
print(' - conflicts : %i' % solver.NumConflicts())
print(' - branches : %i' % solver.NumBranches())
print(' - wall time : %f ms' % solver.WallTime())
print()
if __name__ == "__main__":