Files
ortools-clone/examples/contrib/sicherman_dice.cs
2020-11-03 10:15:53 +01:00

144 lines
4.1 KiB
C#

//
// Copyright 2012 Hakan Kjellerstrand
//
// 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 System.Collections;
using System.Collections.Generic;
using System.Linq;
using Google.OrTools.ConstraintSolver;
public class SichermanDice
{
/**
*
* Sicherman Dice.
*
* From http://en.wikipedia.org/wiki/Sicherman_dice
* ""
* Sicherman dice are the only pair of 6-sided dice which are not normal dice,
* bear only positive integers, and have the same probability distribution for
* the sum as normal dice.
*
* The faces on the dice are numbered 1, 2, 2, 3, 3, 4 and 1, 3, 4, 5, 6, 8.
* ""
*
* I read about this problem in a book/column by Martin Gardner long
* time ago, and got inspired to model it now by the WolframBlog post
* "Sicherman Dice": http://blog.wolfram.com/2010/07/13/sicherman-dice/
*
* This model gets the two different ways, first the standard way and
* then the Sicherman dice:
*
* x1 = [1, 2, 3, 4, 5, 6]
* x2 = [1, 2, 3, 4, 5, 6]
* ----------
* x1 = [1, 2, 2, 3, 3, 4]
* x2 = [1, 3, 4, 5, 6, 8]
*
*
* Extra: If we also allow 0 (zero) as a valid value then the
* following two solutions are also valid:
*
* x1 = [0, 1, 1, 2, 2, 3]
* x2 = [2, 4, 5, 6, 7, 9]
* ----------
* x1 = [0, 1, 2, 3, 4, 5]
* x2 = [2, 3, 4, 5, 6, 7]
*
* These two extra cases are mentioned here:
* http://mathworld.wolfram.com/SichermanDice.html
*
*
* Also see http://www.hakank.org/or-tools/sicherman_dice.py
*
*/
private static void Solve()
{
Solver solver = new Solver("SichermanDice");
//
// Data
//
int n = 6;
int m = 10;
int lowest_value = 0;
// standard distribution
int[] standard_dist = { 1, 2, 3, 4, 5, 6, 5, 4, 3, 2, 1 };
IEnumerable<int> RANGE = Enumerable.Range(0, n);
IEnumerable<int> RANGE1 = Enumerable.Range(0, n - 1);
//
// Decision variables
//
IntVar[] x1 = solver.MakeIntVarArray(n, lowest_value, m, "x1");
IntVar[] x2 = solver.MakeIntVarArray(n, lowest_value, m, "x2");
//
// Constraints
//
for (int k = 0; k < standard_dist.Length; k++)
{
solver.Add((from i in RANGE from j in RANGE select x1[i] + x2[j] == k + 2).ToArray().Sum() ==
standard_dist[k]);
}
// symmetry breaking
foreach (int i in RANGE1)
{
solver.Add(x1[i] <= x1[i + 1]);
solver.Add(x2[i] <= x2[i + 1]);
solver.Add(x1[i] <= x2[i]);
}
//
// Search
//
DecisionBuilder db =
solver.MakePhase(x1.Concat(x2).ToArray(), Solver.INT_VAR_DEFAULT, Solver.INT_VALUE_DEFAULT);
solver.NewSearch(db);
while (solver.NextSolution())
{
Console.Write("x1: ");
foreach (int i in RANGE)
{
Console.Write(x1[i].Value() + " ");
}
Console.Write("\nx2: ");
foreach (int i in RANGE)
{
Console.Write(x2[i].Value() + " ");
}
Console.WriteLine("\n");
}
Console.WriteLine("\nSolutions: {0}", solver.Solutions());
Console.WriteLine("WallTime: {0}ms", solver.WallTime());
Console.WriteLine("Failures: {0}", solver.Failures());
Console.WriteLine("Branches: {0} ", solver.Branches());
solver.EndSearch();
}
public static void Main(String[] args)
{
Solve();
}
}