void Solve(int limit)
{
// Declares the optimization model.
LSModel model = localsolver.GetModel();
trucksUsed = new LSExpression[nbTrucks];
customersSequences = new LSExpression[nbTrucks];
routeDistances = new LSExpression[nbTrucks];
// Sequence of customers visited by each truck.
for (int k = 0; k < nbTrucks; k++)
{
customersSequences[k] = model.List(nbCustomers);
}
// All customers must be visited by the trucks
model.Constraint(model.Partition(customersSequences));
// Create demands and distances as arrays to be able to access it with an "at" operator
LSExpression demandsArray = model.Array(demands);
LSExpression distanceWarehouseArray = model.Array(distanceWarehouses);
LSExpression distanceArray = model.Array(distanceMatrix);
for (int k = 0; k < nbTrucks; k++)
{
LSExpression sequence = customersSequences[k];
LSExpression c = model.Count(sequence);
// A truck is used if it visits at least one customer
trucksUsed[k] = c > 0;
// The quantity needed in each route must not exceed the truck capacity
LSExpression demandSelector = model.Function(i => demandsArray[sequence[i]]);
LSExpression routeQuantity = model.Sum(model.Range(0, c), demandSelector);
model.Constraint(routeQuantity <= truckCapacity);
// Distance travelled by truck k
LSExpression distSelector = model.Function(i => distanceArray[sequence[i - 1], sequence[i]]);
routeDistances[k] = model.Sum(model.Range(1, c), distSelector)
+ model.If(c > 0, distanceWarehouseArray[sequence[0]] + distanceWarehouseArray[sequence[c - 1]], 0);
}
nbTrucksUsed = model.Sum(trucksUsed);
totalDistance = model.Sum(routeDistances);
// Objective: minimize the number of trucks used, then minimize the distance traveled
model.Minimize(nbTrucksUsed);
model.Minimize(totalDistance);
model.Close();
// Parameterizes the solver.
LSPhase phase = localsolver.CreatePhase();
phase.SetTimeLimit(limit);
localsolver.Solve();
}
void Solve(int limit)
{
// Declares the optimization model.
localsolver = new LocalSolver();
LSModel model = localsolver.GetModel();
// Decision variables x[i]
x = new LSExpression[nbItems];
for (int i = 0; i < nbItems; i++)
{
x[i] = model.Bool();
}
// weight constraint
LSExpression knapsackWeight = model.Sum();
for (int i = 0; i < nbItems; i++)
{
knapsackWeight.AddOperand(x[i] * weights[i]);
}
model.Constraint(knapsackWeight <= knapsackBound);
// maximize value
knapsackValue = model.Sum();
for (int i = 0; i < nbItems; i++)
{
knapsackValue.AddOperand(x[i] * values[i]);
}
model.Maximize(knapsackValue);
model.Close();
// Parameterizes the solver.
localsolver.GetParam().SetTimeLimit(limit);
localsolver.Solve();
solutions = new List <int>();
for (int i = 0; i < nbItems; ++i)
{
if (x[i].GetValue() == 1)
{
solutions.Add(i);
}
}
}
public static void Execute()
{
const int numberOfSantas = 2;
const int numberOfVisits = 6;
const int m = int.MaxValue;
var distanceHome = new int[numberOfVisits]
{
0, 0, 0, 0, 0, 0
};
var distance = new int[numberOfVisits][]
{
new int[numberOfVisits] {
m, 3, 6, 2, 8, 1
},
new int[numberOfVisits] {
4, m, 3, 4, 4, 5
},
new int[numberOfVisits] {
3, 2, m, 6, 3, 5
},
new int[numberOfVisits] {
4, 2, 5, m, 4, 4
},
new int[numberOfVisits] {
3, 3, 2, 6, m, 4
},
new int[numberOfVisits] {
7, 4, 5, 7, 6, m
},
};
using (var localsolver = new localsolver.LocalSolver())
{
// Declares the optimization model.
var model = localsolver.GetModel();
var santaUsed = new LSExpression[numberOfSantas];
var visitSequences = new LSExpression[numberOfSantas];
var routeDistances = new LSExpression[numberOfSantas];
// Sequence of customers visited by each truck.
for (int k = 0; k < numberOfSantas; k++)
{
visitSequences[k] = model.List(numberOfVisits);
}
model.Constraint(model.Partition(visitSequences));
// Create demands and distances as arrays to be able to access it with an "at" operator
var distanceArray = model.Array(distance);
var distanceHomeArray = model.Array(distanceHome);
for (int s = 0; s < numberOfSantas; s++)
{
var sequence = visitSequences[s];
var c = model.Count(sequence);
santaUsed[s] = c > 0;
var distSelector = model.Function(i => distanceArray[sequence[i - 1], sequence[i]]);
routeDistances[s] = model.Sum(model.Range(1, c), distSelector)
+ model.If(c > 0, distanceHomeArray[sequence[0]] + distanceHomeArray[sequence[c - 1]], 0);
}
var totalDistance = model.Sum(routeDistances);
// Objective: minimize the number of trucks used, then minimize the distance traveled
//model.Minimize(nbTrucksUsed);
model.Minimize(totalDistance);
model.Close();
// Parameterizes the solver.
var phase = localsolver.CreatePhase();
phase.SetTimeLimit(3);
localsolver.Solve();
// output
for (int i = 0; i < numberOfSantas; i++)
{
System.Console.WriteLine($"santa {i+1}: ");
System.Console.WriteLine(string.Join("->", visitSequences[i].GetCollectionValue()));
}
}
}
public SolverVariables(LSModel model, int numberOfRoutes, List <Visit> visits, int[,] routeCosts, OptimizationInput optimizationInput, int numberOfFakeSantas)
{
Model = model;
Visits = visits;
NumberOfRoutes = numberOfRoutes;
OptimizationInput = optimizationInput;
NumberOfFakeSantas = numberOfFakeSantas;
NumberOfSantas = optimizationInput.Santas.Length;
SantaUsed = new LSExpression[numberOfRoutes];
VisitSequences = new LSExpression[numberOfRoutes + 1];
SantaWalkingTime = new LSExpression[numberOfRoutes];
SantaRouteTime = new LSExpression[numberOfRoutes];
SantaVisitDurations = new LSExpression[numberOfRoutes];
SantaDesiredDuration = new LSExpression[numberOfRoutes];
SantaUnavailableDuration = new LSExpression[numberOfRoutes];
SantaVisitStartingTimes = new LSExpression[numberOfRoutes];
SantaOvertime = new LSExpression[numberOfRoutes];
SantaWaitBeforeStart = new LSExpression[numberOfRoutes];
SantaWaitBetweenVisit = new LSExpression[numberOfRoutes][];
SantaWaitBetweenVisitArray = new LSExpression[numberOfRoutes];
int numberOfVisits = Visits.Count;
var longestDay = OptimizationInput.Days.Max(d => d.to - d.from);
for (var k = 0; k < numberOfRoutes; k++)
{
VisitSequences[k] = Model.List(numberOfVisits);
SantaOvertime[k] = Model.Int(0, int.MaxValue);
SantaWaitBeforeStart[k] = Model.Int(0, longestDay);
SantaWaitBetweenVisit[k] = new LSExpression[numberOfVisits];
for (var i = 0; i < SantaWaitBetweenVisit[k].Length; i++)
{
SantaWaitBetweenVisit[k][i] = Model.Int(0, longestDay);
}
SantaWaitBetweenVisitArray[k] = Model.Array(SantaWaitBetweenVisit[k]);
}
// overflow for unused santa breaks
VisitSequences[numberOfRoutes] = model.List(numberOfVisits);
DistanceArray = model.Array(RouteCostJagged(Visits, routeCosts));
DistanceFromHomeArray = model.Array(Visits.Select(v => v.WayCostFromHome).ToArray());
DistanceToHomeArray = model.Array(Visits.Select(v => v.WayCostToHome).ToArray());
VisitDurationArray = model.Array(Visits.Select(v => v.Duration).ToArray());
// desired
var visitsOnlyDesired = visits
.Select(v =>
// fake arr
v.Desired.Length == 0
? new[] { new[] { -1, -1 } }
: v.Desired.Select(d => new[] { d.from, d.to }).ToArray()
)
.ToArray();
VisitDesiredArray = model.Array(visitsOnlyDesired);
VisitDesiredCountArray = model.Array(visits.Select(v => v.Desired.Length).ToArray());
// unavailable
var visitsOnlyUnavailable = visits
.Select(v =>
// fake arr
v.Unavailable.Length == 0
? new[] { new[] { -1, -1 } }
: v.Unavailable.Select(d => new[] { d.from, d.to }).ToArray()
)
.ToArray();
VisitUnavailableArray = model.Array(visitsOnlyUnavailable);
VisitUnavailableCountArray = model.Array(visits.Select(v => v.Unavailable.Length).ToArray());
}
public static void Execute()
{
const int numberOfSantas = 6;
const int numberOfVisits = 30;
const int m = int.MaxValue;
var distanceHome = new int[numberOfVisits]
{
106, 378, 305, 337, 483, 337, 316, 142, 306, 242, 130, 0, 381, 358, 255, 167, 34, 345, 972, 1116, 1160, 1113, 467, 534, 1073, 956, 937, 1020, 254, 389
};
var distance = new int[numberOfVisits][]
{
new int[numberOfVisits] {
0, 273, 274, 366, 383, 429, 408, 234, 398, 334, 222, 92, 302, 253, 150, 156, 63, 240, 1064, 1208, 1252, 1205, 496, 563, 1165, 1048, 1029, 1112, 264, 418
},
new int[numberOfVisits] {
246, 0, 203, 219, 181, 675, 654, 480, 644, 580, 468, 338, 100, 428, 107, 331, 309, 120, 1310, 1454, 1498, 1451, 416, 483, 1411, 1294, 1275, 1358, 439, 504
},
new int[numberOfVisits] {
268, 215, 0, 180, 207, 621, 600, 426, 590, 526, 340, 284, 105, 450, 184, 353, 255, 264, 1256, 1400, 1444, 1397, 377, 444, 1357, 1240, 1221, 1304, 461, 348
},
new int[numberOfVisits] {
414, 275, 224, 0, 267, 709, 688, 514, 678, 614, 426, 372, 165, 632, 311, 539, 343, 324, 1344, 1488, 1532, 1485, 197, 264, 1445, 1328, 1309, 1392, 626, 311
},
new int[numberOfVisits] {
345, 170, 184, 200, 0, 774, 753, 579, 743, 679, 495, 437, 81, 527, 206, 430, 408, 219, 1409, 1553, 1597, 1550, 293, 360, 1510, 1393, 1374, 1457, 538, 485
},
new int[numberOfVisits] {
480, 753, 680, 712, 858, 0, 186, 236, 176, 355, 443, 375, 756, 733, 630, 525, 409, 720, 1085, 1229, 977, 1008, 842, 909, 1094, 1069, 1050, 1041, 612, 743
},
new int[numberOfVisits] {
441, 714, 641, 673, 819, 161, 0, 224, 8, 262, 404, 336, 717, 694, 591, 486, 370, 681, 992, 1136, 1069, 1100, 803, 870, 1093, 976, 957, 1040, 573, 704
},
new int[numberOfVisits] {
244, 517, 444, 476, 622, 195, 208, 0, 198, 119, 207, 139, 520, 497, 394, 289, 173, 484, 849, 993, 1037, 990, 606, 673, 950, 833, 814, 897, 376, 507
},
new int[numberOfVisits] {
433, 706, 633, 665, 811, 153, 11, 216, 0, 254, 396, 328, 709, 686, 583, 478, 362, 673, 984, 1128, 1061, 1092, 795, 862, 1085, 968, 949, 1032, 565, 696
},
new int[numberOfVisits] {
329, 602, 529, 561, 707, 299, 224, 104, 214, 0, 292, 224, 605, 582, 479, 374, 258, 569, 746, 874, 918, 871, 691, 758, 831, 714, 695, 778, 338, 592
},
new int[numberOfVisits] {
253, 526, 379, 409, 557, 423, 402, 228, 392, 328, 0, 148, 455, 506, 403, 298, 182, 493, 1058, 1202, 1246, 1199, 539, 606, 1159, 1042, 1023, 1106, 385, 393
},
new int[numberOfVisits] {
106, 378, 305, 337, 483, 337, 316, 142, 306, 242, 130, 0, 381, 358, 255, 167, 34, 345, 972, 1116, 1160, 1113, 467, 534, 1073, 956, 937, 1020, 254, 389
}, // depot
new int[numberOfVisits] {
285, 110, 103, 119, 102, 695, 674, 500, 664, 600, 414, 358, 0, 467, 146, 370, 329, 159, 1330, 1474, 1518, 1471, 316, 383, 1431, 1314, 1295, 1378, 478, 404
},
new int[numberOfVisits] {
203, 405, 406, 569, 515, 632, 611, 437, 601, 537, 425, 295, 434, 0, 282, 207, 266, 372, 1267, 1411, 1455, 1408, 699, 766, 1368, 1251, 1232, 1315, 315, 621
},
new int[numberOfVisits] {
139, 123, 179, 271, 233, 568, 547, 373, 537, 473, 361, 231, 152, 321, 0, 224, 202, 90, 1203, 1347, 1391, 1344, 468, 535, 1304, 1187, 1168, 1251, 332, 421
},
new int[numberOfVisits] {
128, 330, 331, 465, 440, 448, 427, 253, 417, 353, 241, 128, 359, 229, 207, 0, 162, 297, 1083, 1227, 1271, 1224, 595, 662, 1184, 1067, 1048, 1131, 108, 517
},
new int[numberOfVisits] {
70, 343, 266, 298, 444, 365, 344, 170, 334, 270, 158, 28, 342, 323, 220, 195, 0, 310, 954, 1098, 1008, 1039, 711, 778, 1055, 938, 919, 1002, 481, 612
},
new int[numberOfVisits] {
217, 124, 256, 272, 234, 646, 625, 451, 615, 551, 439, 309, 153, 399, 78, 302, 280, 0, 1281, 1425, 1469, 1422, 469, 536, 1382, 1265, 1246, 1329, 410, 499
},
new int[numberOfVisits] {
1114, 1387, 1314, 1346, 1522, 1084, 1009, 889, 999, 794, 1077, 1009, 1420, 1367, 1264, 1159, 970, 1354, 0, 245, 316, 269, 1476, 1543, 229, 112, 276, 176, 1052, 1377
},
new int[numberOfVisits] {
1280, 1553, 1480, 1512, 1688, 1250, 1175, 1055, 1165, 951, 1243, 1175, 1586, 1533, 1430, 1325, 1136, 1520, 259, 0, 353, 306, 1642, 1709, 139, 252, 315, 184, 1289, 1543
},
new int[numberOfVisits] {
1355, 1628, 1555, 1587, 1763, 1034, 1145, 1130, 1135, 1026, 1318, 1250, 1661, 1608, 1505, 1400, 1082, 1595, 361, 391, 0, 149, 1532, 1599, 235, 250, 282, 182, 1364, 1540
},
new int[numberOfVisits] {
1311, 1584, 1511, 1543, 1719, 1068, 1179, 1086, 1169, 982, 1274, 1206, 1617, 1564, 1461, 1356, 1116, 1551, 317, 347, 152, 0, 1566, 1633, 191, 206, 238, 138, 1320, 1574
},
new int[numberOfVisits] {
577, 505, 454, 230, 387, 872, 851, 677, 841, 777, 589, 535, 395, 830, 541, 702, 758, 554, 1507, 1651, 1508, 1539, 0, 67, 1608, 1491, 1472, 1555, 789, 474
},
new int[numberOfVisits] {
646, 574, 523, 299, 456, 941, 920, 746, 910, 846, 658, 604, 464, 899, 610, 771, 827, 623, 1576, 1720, 1577, 1608, 69, 0, 1677, 1560, 1541, 1624, 858, 543
},
new int[numberOfVisits] {
1247, 1520, 1447, 1479, 1655, 1130, 1142, 1022, 1132, 918, 1210, 1142, 1553, 1500, 1397, 1292, 1103, 1487, 253, 156, 214, 167, 1609, 1676, 0, 142, 176, 45, 1256, 1510
},
new int[numberOfVisits] {
1125, 1398, 1325, 1357, 1533, 1095, 1020, 900, 1010, 796, 1088, 1020, 1431, 1378, 1275, 1170, 981, 1365, 131, 257, 224, 177, 1487, 1554, 137, 0, 184, 84, 1134, 1388
},
new int[numberOfVisits] {
1109, 1382, 1309, 1341, 1517, 1079, 1004, 884, 994, 780, 1072, 1004, 1415, 1362, 1259, 1154, 965, 1349, 290, 322, 251, 204, 1471, 1538, 166, 179, 0, 113, 1118, 1372
},
new int[numberOfVisits] {
1202, 1475, 1402, 1434, 1610, 1085, 1097, 977, 1087, 873, 1165, 1097, 1508, 1455, 1352, 1247, 1058, 1442, 208, 209, 169, 122, 1564, 1631, 54, 97, 131, 0, 1211, 1465
},
new int[numberOfVisits] {
241, 443, 444, 557, 553, 540, 519, 345, 509, 337, 333, 220, 472, 342, 320, 113, 426, 410, 996, 1211, 1255, 1208, 687, 754, 1168, 1051, 1032, 1115, 0, 609
},
new int[numberOfVisits] {
505, 606, 443, 350, 598, 775, 754, 580, 744, 680, 445, 463, 496, 758, 521, 630, 661, 611, 1410, 1554, 1525, 1551, 480, 547, 1511, 1394, 1375, 1458, 717, 0
},
};
var visitDuration = new int[numberOfVisits]
{
2700,
1500,
2100,
3600,
1500,
1200,
1800,
1500,
1500,
1800,
2100,
0,
1800,
1200,
1500,
1500,
1800,
1500,
1500,
1500,
1500,
1200,
1200,
1500,
1800,
1500,
1500,
1500,
2400,
1500
};
using (var localsolver = new localsolver.LocalSolver())
{
// Declares the optimization model.
var model = localsolver.GetModel();
var santaUsed = new LSExpression[numberOfSantas];
var visitSequences = new LSExpression[numberOfSantas];
var routeDistances = new LSExpression[numberOfSantas];
var santaVisitDurations = new LSExpression[numberOfSantas];
// Sequence of customers visited by each truck.
for (int k = 0; k < numberOfSantas; k++)
{
visitSequences[k] = model.List(numberOfVisits);
}
model.Constraint(model.Partition(visitSequences));
var distanceArray = model.Array(distance);
var distanceHomeArray = model.Array(distanceHome);
var visitDurationArray = model.Array(visitDuration);
for (int s = 0; s < numberOfSantas; s++)
{
var sequence = visitSequences[s];
var c = model.Count(sequence);
santaUsed[s] = c > 0;
var distSelector = model.Function(i => distanceArray[sequence[i - 1], sequence[i]] + visitDurationArray[i]);
var visitSelector = model.Function(i => visitDurationArray[i]);
routeDistances[s] = model.Sum(model.Range(1, c), distSelector)
+ model.If(santaUsed[s], distanceHomeArray[sequence[0]] + distanceHomeArray[sequence[c - 1]], 0);
santaVisitDurations[s] = model.Sum(model.Range(1, c), visitSelector);
model.Constraint(routeDistances[s] <= (21 - 17) * 60 * 60); // working hours from 17:00 to 21:00
}
var totalDistance = model.Sum(routeDistances);
// model.Minimize(totalDistance);
// every santa same visit duration:
var totalDuration = visitDuration.Sum();
var numberOfSantasUsed = model.Sum(santaUsed);
var avgDists = new LSExpression[numberOfSantas];
for (int s = 0; s < numberOfSantas; s++)
{
avgDists[s] = model.Abs(santaVisitDurations[s] -
(totalDuration / numberOfSantasUsed));
}
var avgTime = model.Sum(avgDists);
model.Minimize(avgTime * 5 + totalDistance);
model.Close();
// Parameterizes the solver.
var phase = localsolver.CreatePhase();
phase.SetTimeLimit(500);
localsolver.Solve();
// output
for (int i = 0; i < numberOfSantas; i++)
{
System.Console.WriteLine($"santa {i + 1}: ");
System.Console.WriteLine(string.Join("->", visitSequences[i].GetCollectionValue()));
System.Console.WriteLine($"route distance: {routeDistances[i].GetValue()}");
}
}
}