Google OR-Tools v9.11
a fast and portable software suite for combinatorial optimization
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dualizer.h
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1// Copyright 2010-2024 Google LLC
2// Licensed under the Apache License, Version 2.0 (the "License");
3// you may not use this file except in compliance with the License.
4// You may obtain a copy of the License at
5//
6// http://www.apache.org/licenses/LICENSE-2.0
7//
8// Unless required by applicable law or agreed to in writing, software
9// distributed under the License is distributed on an "AS IS" BASIS,
10// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
11// See the License for the specific language governing permissions and
12// limitations under the License.
13
14#ifndef OR_TOOLS_MATH_OPT_LABS_DUALIZER_H_
15#define OR_TOOLS_MATH_OPT_LABS_DUALIZER_H_
16
17#include <utility>
18#include <vector>
19
20#include "absl/types/span.h"
22
23namespace operations_research {
24namespace math_opt {
25
26// Uses LP duality to construct an extended formulation of
27//
28// max_w{ a(w) * x : w in W} <= rhs
29//
30// where W is described by uncertainty_model (the variables of uncertainty_model
31// are w). All the variables and constraints of the extended formulation are
32// added to main_model.
33//
34// Requirements:
35// * x must be variables of main_model
36// * rhs must be a variable of main_model
37// * uncertainty_model must be an LP
38// * uncertain coefficient a(w)_i for x_i should be a LinearExpression of w.
39//
40// Input-only arguments:
41// * uncertainty_model
42// * rhs
43// * uncertain_coefficients: pairs [a(w)_i, x_i] for all i
44// Input-output argument:
45// * main_model
46void AddRobustConstraint(const Model& uncertainty_model, Variable rhs,
47 absl::Span<const std::pair<LinearExpression, Variable>>
48 uncertain_coefficients,
49 Model& main_model);
50
51} // namespace math_opt
52} // namespace operations_research
53#endif // OR_TOOLS_MATH_OPT_LABS_DUALIZER_H_
void AddRobustConstraint(const Model &uncertainty_model, const Variable rhs, absl::Span< const std::pair< LinearExpression, Variable > > uncertain_coefficients, Model &main_model)
Definition dualizer.cc:202
In SWIG mode, we don't want anything besides these top-level includes.