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cp_model_objective.cc
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cp_model_objective.cc
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// Copyright 2010-2021 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.
#include "ortools/sat/cp_model_objective.h"
#include <cstdint>
#include "ortools/sat/cp_model_utils.h"
namespace operations_research {
namespace sat {
void EncodeObjectiveAsSingleVariable(CpModelProto* cp_model) {
if (!cp_model->has_objective()) return;
if (cp_model->objective().vars_size() == 1) {
// Canonicalize the objective to make it easier on us by always making the
// coefficient equal to 1.0.
const int old_ref = cp_model->objective().vars(0);
const int64_t old_coeff = cp_model->objective().coeffs(0);
const double muliplier = static_cast<double>(std::abs(old_coeff));
if (old_coeff < 0) {
cp_model->mutable_objective()->set_vars(0, NegatedRef(old_ref));
}
if (muliplier != 1.0) {
// TODO(user): deal with this case.
CHECK(cp_model->objective().domain().empty());
double old_factor = cp_model->objective().scaling_factor();
if (old_factor == 0.0) old_factor = 1.0;
const double old_offset = cp_model->objective().offset();
cp_model->mutable_objective()->set_scaling_factor(old_factor * muliplier);
cp_model->mutable_objective()->set_offset(old_offset / muliplier);
}
cp_model->mutable_objective()->set_coeffs(0, 1.0);
return;
}
// Compute trivial bounds on the objective, this is needed otherwise the
// overflow checker might not be happy with the new constraint we are about
// to create. Note that the model validator should make sure that there is no
// overflow in the computation below.
int64_t min_obj = 0;
int64_t max_obj = 0;
for (int i = 0; i < cp_model->objective().vars_size(); ++i) {
const int ref = cp_model->objective().vars(i);
const int var = PositiveRef(ref);
const int64_t coeff =
cp_model->objective().coeffs(i) * (RefIsPositive(ref) ? 1 : -1);
const int64_t value1 = cp_model->variables(var).domain(0) * coeff;
const int64_t value2 = cp_model->variables(var).domain(
cp_model->variables(var).domain_size() - 1) *
coeff;
min_obj += std::min(value1, value2);
max_obj += std::max(value1, value2);
}
// Create the new objective var.
const int obj_ref = cp_model->variables_size();
{
IntegerVariableProto* obj = cp_model->add_variables();
Domain obj_domain(min_obj, max_obj);
if (!cp_model->objective().domain().empty()) {
obj_domain = obj_domain.IntersectionWith(
ReadDomainFromProto(cp_model->objective()));
}
FillDomainInProto(obj_domain, obj);
}
// Add the linear constraint.
LinearConstraintProto* ct = cp_model->add_constraints()->mutable_linear();
ct->add_domain(0);
ct->add_domain(0);
*(ct->mutable_vars()) = cp_model->objective().vars();
*(ct->mutable_coeffs()) = cp_model->objective().coeffs();
ct->add_vars(obj_ref);
ct->add_coeffs(-1);
// Update the objective.
cp_model->mutable_objective()->clear_vars();
cp_model->mutable_objective()->clear_coeffs();
cp_model->mutable_objective()->add_vars(obj_ref);
cp_model->mutable_objective()->add_coeffs(1);
cp_model->mutable_objective()->clear_domain();
}
} // namespace sat
} // namespace operations_research