70 lines
2.5 KiB
Python
70 lines
2.5 KiB
Python
# Copyright 2010 Pierre Schaus pschaus@gmail.com
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from constraint_solver import pywrapcp
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from time import time
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from random import randint
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#----------------helper for binpacking posting----------------
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def binpacking(cp,binvars,weights,loadvars):
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'''post the connstraints forall j: loadvars[j] == sum_i (binvars[i] == j) * weights[i])'''
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nbins = len(loadvars)
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nitems = len(binvars)
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for j in range(nbins):
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b = [cp.BoolVar(str(i)) for i in range(nitems)]
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for i in range(nitems):
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cp.Add(cp.IsEqualCstCt(binvars[i],j,b[i]))
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cp.Add(solver.Sum([b[i]*weights[i] for i in range(nitems)]) == l[j])
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cp.Add(solver.Sum(loadvars) == sum(weights))
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#------------------------------data reading-------------------
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maxcapa = 44
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weights = [4, 22, 9, 5, 8, 3, 3, 4, 7, 7, 3]
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loss = [0, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, 1, 0, 2, 1, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 2, 1, 0, 3, 2, 1, 0, 2, 1, 0, 0, 0]
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nbslab = 11
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#------------------solver and variable declaration-------------
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solver = pywrapcp.Solver('Steel Mill Slab')
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x = [solver.IntVar(range(nbslab),'x'+str(i)) for i in range(nbslab)]
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l = [solver.IntVar(range(maxcapa),'l'+str(i)) for i in range(nbslab)]
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obj = solver.IntVar(range(nbslab*maxcapa),'obj')
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#-------------------post of the constraints--------------
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binpacking(solver,x,weights[:nbslab],l)
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solver.Add(solver.Sum([solver.Element(loss,l[s]) for s in range(nbslab)]) == obj)
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sol = [2, 0, 0, 0, 0, 1, 2, 2, 1, 1, 2]
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#------------start the search and optimization-----------
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objective = solver.Minimize(obj,1)
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db = solver.Phase(x, solver.INT_VAR_DEFAULT,
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solver.INT_VALUE_DEFAULT)
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#solver.NewSearch(db,[objective]) #segfault if I comment this
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while solver.NextSolution():
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print obj,"check:",sum([loss[l[s].Min()] for s in range(nbslab)])
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print l
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solver.EndSearch()
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print "#fails:",solver.failures()
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print "time:",solver.wall_time()
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