public Annealing(string path)
{
seatInfo = new SeatInfo();
seatInfo.ReadFile(path);
bestSoFar = new SeatingChart(seatInfo);
bestSoFar.RandomChart();
}
/// <summary>
/// Recursive tree traverse used in complete search
/// </summary>
/// <param name="si">SeatInfo contains seating information</param>
/// <param name="temp">current (can be incomplete) temporary seating chart</param>
/// <param name="p">current position in chart</param>
private static void CompleteSearchChart(SeatInfo si, int[] temp, int p)
{
if (p > si.size)
{
if (si.Score(temp) > score)
{
score = si.Score(temp);
chart = new int[temp.Length];
for (int i = 0; i < temp.Length; ++i)
{
chart[i] = temp[i];
}
}
return;
}
for (int i = 1; i <= si.size; ++i)
{
if (Check(temp, p, i))
{
temp[p] = i;
CompleteSearchChart(si, temp, p + 1);
}
}
}
public Annealing(string path)
{
seatInfo = new SeatInfo();
seatInfo.ReadFile(path);
bestSoFar = new SeatingChart(seatInfo);
bestSoFar.RandomChart();
}
/// <summary>
/// Perform a local search with random move 50% of the time
/// </summary>
/// <param name="si">Seating info used to grade the seating scheme</param>
static void StochasticSearch(SeatInfo si)
{
DateTime due = DateTime.Now.AddMinutes(1);
System.IO.StreamWriter debug = new System.IO.StreamWriter(@"..\..\debug.txt");
int[] temp = AssignRandomSeat(si.size);
int tempScore = si.Score(temp);
DateTime t = DateTime.Now;
int n = 0; //how many time a move results in a suboptimal score / no good move is found
while (t <= due)
{
if (n == 0 || t.Millisecond % 2 == 0) // perform the "good" move if the last good-move attempt wasn't stuck
{
GoodMove(si, ref temp, ref tempScore);
if (tempScore > score)
{
Array.Copy(temp, chart, si.size + 1);
score = tempScore;
n = 0;
}
else
{
++n;
}
}
else
{
RandomMove(si, ref temp, ref tempScore);
if (tempScore > score)
{
Array.Copy(temp, chart, si.size + 1);
score = tempScore;
n = 0;
}
else
{
++n;
}
}
if (n > 100) // stuck for the last 100 moves then restart
{
temp = AssignRandomSeat(si.size);
tempScore = si.Score(temp);
debug.WriteLine("Resetted!");
}
t = DateTime.Now;
}
debug.Close();
}
/// <summary>
/// Perform a random move
/// </summary>
/// <param name="si">Seating info to grade the new scheme</param>
/// <param name="temp">current seating scheme</param>
/// <param name="tempScore">current score</param>
private static void RandomMove(SeatInfo si, ref int[] temp, ref int tempScore)
{
Random rand = new Random();
int i = rand.Next(si.size) + 1;
int j;
do
{
j = rand.Next(si.size) + 1;
} while (i == j);
Swap(ref temp, i, j);
tempScore = si.Score(temp);
}
/// <summary>
/// Perform a good move: look for the neighbour with the highest score
/// </summary>
/// <param name="si">seating info to grade the scheme</param>
/// <param name="temp">current seating scheme</param>
/// <param name="tempScore">current score</param>
private static void GoodMove(SeatInfo si, ref int[] temp, ref int tempScore)
{
int seatToSwap1 = 0, seatToSwap2 = 0;
for (int i = 1; i <= si.size; ++i)
{
for (int j = i + 1; j <= si.size; ++j)
{
Swap(ref temp, i, j);
if (si.Score(temp) > tempScore)
{
seatToSwap1 = i;
seatToSwap2 = j;
tempScore = si.Score(temp);
}
Swap(ref temp, i, j);
}
}
if (seatToSwap1 != 0 && seatToSwap2 != 0)
{
Swap(ref temp, seatToSwap1, seatToSwap2);
}
tempScore = si.Score(temp);
}
public Annealing(SeatInfo si)
{
seatInfo = si;
bestSoFar = new SeatingChart(si);
bestSoFar.InitializeChart();
}
public SeatingChart(SeatInfo si)
{
seatInfo = si;
this.size = si.size;
chart = new int[size + 1];
}
public Annealing(SeatInfo si)
{
seatInfo = si;
bestSoFar = new SeatingChart(si);
bestSoFar.InitializeChart();
}
public SeatingChart(SeatInfo si)
{
seatInfo = si;
this.size = si.size;
chart = new int[size + 1];
}
/// <summary>
/// Perform a complete search based on info given by si to find the optimal configuration
/// </summary>
/// <param name="si">Seat info given</param>
static void CompleteSearch(SeatInfo si)
{
int[] temp = new int[si.size + 1];
CompleteSearchChart(si, temp, 1);
}
static void Main(string[] args)
{
DateTime start = DateTime.Now;
if (args.Length == 0)
{
Console.WriteLine("Argument: ");
Console.WriteLine("c <file>: complete space state search using seating info from <file>");
Console.WriteLine("l <file>: local search using seating info from <file>");
Console.WriteLine("s <file>: stimulated annealing using seating info from <file>");
Console.WriteLine("a <file>: auto mode. Will try the most suitable search method");
return;
}
SeatInfo si = new SeatInfo();
si.ReadFile(args[1]);
chart = new int[si.size + 1];
score = 0;
switch (args[0])
{
case "c":
Console.Write("Complete search...");
CompleteSearch(si);
break;
case "l":
Console.Write("Local search... ");
StochasticSearch(si);
break;
case "s":
Console.WriteLine("Stimulated annealing... ");
Annealing sa = new Annealing(si);
SeatingChart sc = sa.Anneal();
Array.Copy(sc.chart, chart, sc.size + 1);
score = sc.score;
break;
case "a":
if (si.size <= 11)
{
Console.Write("Complete search...");
CompleteSearch(si);
}
else
{
Console.Write("Local search... ");
StochasticSearch(si);
}
break;
default:
Console.WriteLine("Argument: ");
Console.WriteLine("c <file>: complete space state search using seating info from <file>");
Console.WriteLine("l <file>: local search using seating info from <file>");
Console.WriteLine("s <file>: stimulated annealing using seating info from <file>");
Console.WriteLine("a <file>: auto mode. Will try the most suitable search method");
return;
}
if (debug)
{
si.Display();
}
Console.WriteLine(" finished!");
DisplaySeatingChart(chart, score);
Console.WriteLine("Run time: " + (DateTime.Now - start));
//int[] a = AssignRandomSeat(10);
//for (int i = 1; i <= 10; ++i)
//{
// Console.Write(a[i] + ", ");
//}
Console.ReadLine();
}