Files
ortools-clone/ortools/algorithms/csharp/KnapsackSolverTests.cs
Corentin Le Molgat a66a6daac7 Bump Copyright to 2025
2025-01-10 11:35:44 +01:00

115 lines
4.3 KiB
C#

// Copyright 2010-2025 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 Xunit;
using Google.OrTools.Algorithms;
namespace Google.OrTools.Tests
{
public class KnapsakSolverTest
{
private long RunKnapsackSolver(KnapsackSolver.SolverType solverType, long[] profits, long[,] weights,
long[] capacities)
{
KnapsackSolver solver = new KnapsackSolver(solverType, "test");
Assert.NotNull(solver);
solver.Init(profits, weights, capacities);
return solver.Solve();
}
private void SolveKnapsackProblem(long[] profits, long[,] weights, long[] capacities, long optimalProfit)
{
int maxNumberOfItemsForBruteForce = 20;
int maxNumberOfItemsForDivideAndConquer = 32;
int maxNumberOfItemsFor64ItemsSolver = 64;
{
long profit = RunKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_MULTIDIMENSION_BRANCH_AND_BOUND_SOLVER,
profits, weights, capacities);
Assert.Equal(optimalProfit, profit);
}
// Other solvers don't support multidimension models.
if (weights.Length > 1)
{
return;
}
int numOfItems = profits.Length;
if (numOfItems <= maxNumberOfItemsForBruteForce)
{
long profit =
RunKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_BRUTE_FORCE_SOLVER, profits, weights, capacities);
Assert.Equal(optimalProfit, profit);
}
if (numOfItems <= maxNumberOfItemsForDivideAndConquer)
{
long profit = RunKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_DIVIDE_AND_CONQUER_SOLVER, profits,
weights, capacities);
Assert.Equal(optimalProfit, profit);
}
{
long profit = RunKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_DYNAMIC_PROGRAMMING_SOLVER, profits,
weights, capacities);
Assert.Equal(optimalProfit, profit);
}
if (numOfItems <= maxNumberOfItemsFor64ItemsSolver)
{
long profit =
RunKnapsackSolver(KnapsackSolver.SolverType.KNAPSACK_64ITEMS_SOLVER, profits, weights, capacities);
Assert.Equal(optimalProfit, profit);
}
}
[Fact]
public void SolveOneDimension()
{
long[] profits = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
long[,] weights = { { 1, 2, 3, 4, 5, 6, 7, 8, 9 } };
long[] capacities = { 34 };
long optimalProfit = 34;
SolveKnapsackProblem(profits, weights, capacities, optimalProfit);
}
[Fact]
public void SolveTwoDimensions()
{
long[] profits = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
long[,] weights = { { 1, 2, 3, 4, 5, 6, 7, 8, 9 }, { 1, 1, 1, 1, 1, 1, 1, 1, 1 } };
long[] capacities = { 34, 4 };
long optimalProfit = 30;
SolveKnapsackProblem(profits, weights, capacities, optimalProfit);
}
[Fact]
public void SolveBigOneDimension()
{
long[] profits = { 360, 83, 59, 130, 431, 67, 230, 52, 93, 125, 670, 892, 600, 38, 48, 147, 78,
256, 63, 17, 120, 164, 432, 35, 92, 110, 22, 42, 50, 323, 514, 28, 87, 73,
78, 15, 26, 78, 210, 36, 85, 189, 274, 43, 33, 10, 19, 389, 276, 312 };
long[,] weights = { { 7, 0, 30, 22, 80, 94, 11, 81, 70, 64, 59, 18, 0, 36, 3, 8, 15,
42, 9, 0, 42, 47, 52, 32, 26, 48, 55, 6, 29, 84, 2, 4, 18, 56,
7, 29, 93, 44, 71, 3, 86, 66, 31, 65, 0, 79, 20, 65, 52, 13 } };
long[] capacities = { 850 };
long optimalProfit = 7534;
SolveKnapsackProblem(profits, weights, capacities, optimalProfit);
}
}
} // namespace Google.OrTools.Tests