102 lines
3.0 KiB
Python
102 lines
3.0 KiB
Python
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# Copyright 2010-2017 Google
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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 ortools.sat.python import cp_model
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def main():
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model = cp_model.CpModel()
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jobs = [[3, 3],
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[2, 5],
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[1, 3],
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[3, 7],
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[7, 3],
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[2, 2],
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[2, 2],
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[5, 5],
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[10, 2],
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[4, 3],
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[2, 6],
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[1, 2],
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[6, 8],
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[4, 5],
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[3, 7]]
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max_length = 10
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horizon = sum(t[0] for t in jobs)
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num_jobs = len(jobs)
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all_jobs = range(num_jobs)
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intervals = []
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intervals0 = []
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intervals1 = []
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performed = []
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starts = []
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ends = []
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demands = []
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for i in all_jobs:
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start = model.NewIntVar(0, horizon, 'start_%i' % i)
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duration = jobs[i][0]
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end = model.NewIntVar(0, horizon, 'end_%i' % i)
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interval = model.NewIntervalVar(start, duration, end, 'interval_%i' % i)
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starts.append(start)
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intervals.append(interval)
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ends.append(end)
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demands.append(jobs[i][1])
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performed_on_m0 = model.NewBoolVar('perform_%i_on_m0' % i)
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performed.append(performed_on_m0)
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start0 = model.NewIntVar(0, horizon, 'start_%i_on_m0' % i)
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end0 = model.NewIntVar(0, horizon, 'end_%i_on_m0' % i)
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interval0 = model.NewOptionalIntervalVar(
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start0, duration, end0, performed_on_m0, 'interval_%i_on_m0' % i)
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intervals0.append(interval0)
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start1 = model.NewIntVar(0, horizon, 'start_%i_on_m1' % i)
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end1 = model.NewIntVar(0, horizon, 'end_%i_on_m1' % i)
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interval1 = model.NewOptionalIntervalVar(
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start1, duration, end1, performed_on_m0.Not(), 'interval_%i_on_m1' % i)
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intervals1.append(interval1)
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# We only propagate the constraint if the tasks is performed on the machine.
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model.Add(start0 == start).OnlyEnforceIf(performed_on_m0)
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model.Add(start1 == start).OnlyEnforceIf(performed_on_m0.Not())
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# Max Length constraint (modeled as a cumulative)
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model.AddCumulative(intervals, demands, max_length)
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# Choose which machine to perform the jobs on.
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model.AddNoOverlap(intervals0)
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model.AddNoOverlap(intervals1)
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# Objective variable.
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makespan = model.NewIntVar(0, horizon, 'makespan')
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model.AddMaxEquality(makespan, ends)
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model.Minimize(makespan)
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# Solve model.
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solver = cp_model.CpSolver()
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solver.Solve(model)
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print('Makespan = %i' % solver.ObjectiveValue())
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for i in all_jobs:
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performed_machine = 1 - solver.Value(performed[i])
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start = solver.Value(starts[i])
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print('Job %i starts at %i on machine %i' % (i, start, performed_machine))
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if __name__ == '__main__':
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main()
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