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SolverHelper.cs
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SolverHelper.cs
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// Copyright 2010-2018 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.
namespace Google.OrTools.LinearSolver {
using System;
using System.Collections.Generic;
// Patch the MPSolver class to:
// - support custom versions of the array-based APIs (MakeVarArray, etc).
// - customize the construction, and the OptimizationProblemType enum.
// - support the natural language API.
public partial class Solver {
public Variable[] MakeVarArray(int count,
double lb,
double ub,
bool integer) {
Variable[] array = new Variable[count];
for (int i = 0; i < count; ++i) {
array[i] = MakeVar(lb, ub, integer, "");
}
return array;
}
public Variable[] MakeVarArray(int count,
double lb,
double ub,
bool integer,
string var_name) {
Variable[] array = new Variable[count];
for (int i = 0; i < count; ++i) {
array[i] = MakeVar(lb, ub, integer, var_name + i);
}
return array;
}
public Variable[,] MakeVarMatrix(int rows,
int cols,
double lb,
double ub,
bool integer) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
matrix[i,j] = MakeVar(lb, ub, integer, "");
}
}
return matrix;
}
public Variable[,] MakeVarMatrix(int rows,
int cols,
double lb,
double ub,
bool integer,
string name) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
string var_name = name + "[" + i + ", " + j +"]";
matrix[i,j] = MakeVar(lb, ub, integer, var_name);
}
}
return matrix;
}
public Variable[] MakeNumVarArray(int count, double lb, double ub) {
return MakeVarArray(count, lb, ub, false);
}
public Variable[] MakeNumVarArray(int count,
double lb,
double ub,
string var_name) {
return MakeVarArray(count, lb, ub, false, var_name);
}
public Variable[,] MakeNumVarMatrix(int rows,
int cols,
double lb,
double ub) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
matrix[i,j] = MakeNumVar(lb, ub, "");
}
}
return matrix;
}
public Variable[,] MakeNumVarMatrix(int rows,
int cols,
double lb,
double ub,
string name) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
string var_name = name + "[" + i + ", " + j +"]";
matrix[i,j] = MakeNumVar(lb, ub, var_name);
}
}
return matrix;
}
public Variable[] MakeIntVarArray(int count, double lb, double ub) {
return MakeVarArray(count, lb, ub, true);
}
public Variable[] MakeIntVarArray(int count,
double lb,
double ub,
string var_name) {
return MakeVarArray(count, lb, ub, true, var_name);
}
public Variable[,] MakeIntVarMatrix(int rows,
int cols,
double lb,
double ub) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
matrix[i,j] = MakeIntVar(lb, ub, "");
}
}
return matrix;
}
public Variable[,] MakeIntVarMatrix(int rows,
int cols,
double lb,
double ub,
string name) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
string var_name = name + "[" + i + ", " + j +"]";
matrix[i,j] = MakeIntVar(lb, ub, var_name);
}
}
return matrix;
}
public Variable[] MakeBoolVarArray(int count) {
return MakeVarArray(count, 0.0, 1.0, true);
}
public Variable[] MakeBoolVarArray(int count, string var_name) {
return MakeVarArray(count, 0.0, 1.0, true, var_name);
}
public Variable[,] MakeBoolVarMatrix(int rows, int cols) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
matrix[i,j] = MakeBoolVar("");
}
}
return matrix;
}
public Variable[,] MakeBoolVarMatrix(int rows, int cols, string name) {
Variable[,] matrix = new Variable[rows, cols];
for (int i = 0; i < rows; ++i) {
for (int j = 0; j < cols; ++j) {
string var_name = name + "[" + i + ", " + j +"]";
matrix[i,j] = MakeBoolVar(var_name);
}
}
return matrix;
}
public static int GetSolverEnum(String solverType) {
System.Reflection.FieldInfo fieldInfo =
typeof(Solver).GetField(solverType);
if (fieldInfo != null) {
return (int)fieldInfo.GetValue(null);
} else {
throw new System.ApplicationException("Solver not supported");
}
}
public static Solver CreateSolver(String name, String type) {
Solver.OptimizationProblemType solver_type =
Solver.OptimizationProblemType.GLOP_LINEAR_PROGRAMMING;
if (Enum.TryParse(type, true, out solver_type)) {
return new Solver(name, solver_type);
} else {
return null;
}
}
public Constraint Add(LinearConstraint constraint) {
return constraint.Extract(this);
}
public void Minimize(LinearExpr expr)
{
Objective().Clear();
Objective().SetMinimization();
Dictionary<Variable, double> coefficients =
new Dictionary<Variable, double>();
double constant = expr.Visit(coefficients);
foreach (KeyValuePair<Variable, double> pair in coefficients)
{
Objective().SetCoefficient(pair.Key, pair.Value);
}
Objective().SetOffset(constant);
}
public void Maximize(LinearExpr expr)
{
Objective().Clear();
Objective().SetMaximization();
Dictionary<Variable, double> coefficients =
new Dictionary<Variable, double>();
double constant = expr.Visit(coefficients);
foreach (KeyValuePair<Variable, double> pair in coefficients)
{
Objective().SetCoefficient(pair.Key, pair.Value);
}
Objective().SetOffset(constant);
}
public void Minimize(Variable var)
{
Objective().Clear();
Objective().SetMinimization();
Objective().SetCoefficient(var, 1.0);
}
public void Maximize(Variable var)
{
Objective().Clear();
Objective().SetMaximization();
Objective().SetCoefficient(var, 1.0);
}
}
} // namespace Google.OrTools.LinearSolver