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EarlinessTardinessCostSampleSat.cs
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EarlinessTardinessCostSampleSat.cs
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// Copyright 2010-2024 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
using System;
using Google.OrTools.Sat;
using Google.OrTools.Util;
public class VarArraySolutionPrinter : CpSolverSolutionCallback
{
public VarArraySolutionPrinter(IntVar[] variables)
{
variables_ = variables;
}
public override void OnSolutionCallback()
{
{
foreach (IntVar v in variables_)
{
Console.Write(String.Format("{0}={1} ", v.ToString(), Value(v)));
}
Console.WriteLine();
}
}
private IntVar[] variables_;
}
public class EarlinessTardinessCostSampleSat
{
static void Main()
{
long earliness_date = 5;
long earliness_cost = 8;
long lateness_date = 15;
long lateness_cost = 12;
// Create the CP-SAT model.
CpModel model = new CpModel();
// Declare our primary variable.
IntVar x = model.NewIntVar(0, 20, "x");
// Create the expression variable and implement the piecewise linear
// function.
//
// \ /
// \______/
// ed ld
//
long large_constant = 1000;
IntVar expr = model.NewIntVar(0, large_constant, "expr");
// Link together expr and x through s1, s2, and s3.
model.AddMaxEquality(expr, new LinearExpr[] { earliness_cost * (earliness_date - x), model.NewConstant(0),
lateness_cost * (x - lateness_date) });
// Search for x values in increasing order.
model.AddDecisionStrategy(new IntVar[] { x }, DecisionStrategyProto.Types.VariableSelectionStrategy.ChooseFirst,
DecisionStrategyProto.Types.DomainReductionStrategy.SelectMinValue);
// Create the solver.
CpSolver solver = new CpSolver();
// Force solver to follow the decision strategy exactly.
// Tell the solver to search for all solutions.
solver.StringParameters = "search_branching:FIXED_SEARCH, enumerate_all_solutions:true";
VarArraySolutionPrinter cb = new VarArraySolutionPrinter(new IntVar[] { x, expr });
solver.Solve(model, cb);
}
}