forked from google/or-tools
-
Notifications
You must be signed in to change notification settings - Fork 0
/
coins_grid.cs
117 lines (101 loc) · 3.04 KB
/
coins_grid.cs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
//
// 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 Google.OrTools.ConstraintSolver;
public class CoinsGrid
{
/**
*
* Solves the Coins Grid problm.
* See http://www.hakank.org/google_or_tools/coins_grid.py
*
*/
private static void Solve(int n = 31, int c = 14)
{
Solver solver = new Solver("CoinsGrid");
//
// Decision variables
//
IntVar[,] x = solver.MakeIntVarMatrix(n, n, 0, 1, "x");
IntVar[] x_flat = x.Flatten();
//
// Constraints
//
// sum row/columns == c
for (int i = 0; i < n; i++)
{
IntVar[] row = new IntVar[n];
IntVar[] col = new IntVar[n];
for (int j = 0; j < n; j++)
{
row[j] = x[i, j];
col[j] = x[j, i];
}
solver.Add(row.Sum() == c);
solver.Add(col.Sum() == c);
}
// quadratic horizonal distance
IntVar[] obj_tmp = new IntVar[n * n];
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
obj_tmp[i * n + j] = (x[i, j] * (i - j) * (i - j)).Var();
}
}
IntVar obj_var = obj_tmp.Sum().Var();
//
// Objective
//
OptimizeVar obj = obj_var.Minimize(1);
//
// Search
//
DecisionBuilder db = solver.MakePhase(x_flat, Solver.CHOOSE_FIRST_UNBOUND, Solver.ASSIGN_MAX_VALUE);
solver.NewSearch(db, obj);
while (solver.NextSolution())
{
Console.WriteLine("obj: " + obj_var.Value());
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
Console.Write(x[i, j].Value() + " ");
}
Console.WriteLine();
}
Console.WriteLine();
}
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)
{
int n = 31;
int c = 14;
if (args.Length > 0)
{
n = Convert.ToInt32(args[0]);
}
if (args.Length > 1)
{
c = Convert.ToInt32(args[1]);
}
Solve(n, c);
}
}