public Solution Run()
{
var stopwatch = Stopwatch.StartNew();
var totalSecondsElapsed = 0.0;
var currentSolution = new HSolver(_dataset).Run();
var temperature = Config.GetSimulatedAnnealingParam().InitialTemperature;
var alpha = Config.GetSimulatedAnnealingParam().Alpha;
var iterationCount = Config.GetSimulatedAnnealingParam().IterationCount;
var diversifyForEachNIteration = Config.GetDiversificationParam().DiversifyForEachNIteration;
var minCustomersToRemove = Config.GetDiversificationParam().MinCustomersToRemove;
var maxCustomersToRemove = Config.GetDiversificationParam().MaxCustomersToRemove;
_bestSolution = currentSolution;
for (var i = 0; i <= iterationCount; i++)
{
totalSecondsElapsed += stopwatch.Elapsed.Milliseconds;
if (i % diversifyForEachNIteration == 0)
{
currentSolution = new Diversifier(currentSolution, minCustomersToRemove, maxCustomersToRemove).Diverisfy();
}
var solutionPool = new List <Solution>();
solutionPool.AddRange(new TwoOptOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new ExchangeOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new RelocateOperator(currentSolution).GenerateFeasibleSolutions());
var candidateSolution = Helpers.GetBestNeighbour(solutionPool);
Console.WriteLine("Iteration: {0}, Time Elapsed: {1} sn, Temp: {2}, {3} candidate, Current Cost: {4}, Best Cost {5}",
i,
totalSecondsElapsed / 1_000.0,
Math.Round(temperature, 3),
solutionPool.Count,
Math.Round(currentSolution.Cost, 3),
Math.Round(_bestSolution.Cost, 3)
);
var currentCost = currentSolution.Cost;
var candidateCost = candidateSolution.Cost;
//var rand = new Random().NextDouble();
//var threshold = GetThreshold(currentCost, candidateCost, temperature);
var acceptanceCondition = candidateCost < currentCost; //||
//(candidateCost >= currentCost && rand <= threshold);
if (acceptanceCondition)
{
currentSolution = Helpers.Clone(candidateSolution);
if (currentSolution.Cost < _bestSolution.Cost)
{
_bestSolution = currentSolution;
}
}
temperature *= alpha;
}
stopwatch.Stop();
return(_bestSolution);
}
public Solution Run()
{
var stopwatch = Stopwatch.StartNew();
var totalSecondsElapsed = 0.0;
var currentSolution = new LocalSearch(_dataset).Run();
var heuristicParams = Config.GetHeuristicsParam();
var iterationCount = heuristicParams.IterationCount;
var tabuListSize = heuristicParams.TabuSearchParam.TabuListSize;
var numberOfNonImprovingIters = heuristicParams.DiversificationParam.NumberOfNonImprovingIters;
var minCustomersToRemove = heuristicParams.DiversificationParam.MinCustomersToRemove;
var maxCustomersToRemove = heuristicParams.DiversificationParam.MaxCustomersToRemove;
var numberOfNonImprovingItersCounter = 0;
var tabuList = new Helpers.FixedSizedQueue <string>(tabuListSize);
_bestSolution = currentSolution;
currentSolution = new Diversifier(Helpers.Clone(_bestSolution), minCustomersToRemove, maxCustomersToRemove).Diverisfy();
tabuList.Enqueue(Helpers.GetStringFormOfSolution(currentSolution));
for (var i = 0; i <= iterationCount; i++)
{
totalSecondsElapsed += stopwatch.Elapsed.Milliseconds;
if (numberOfNonImprovingItersCounter == numberOfNonImprovingIters)
{
currentSolution = new Diversifier(Helpers.Clone(_bestSolution), minCustomersToRemove, maxCustomersToRemove).Diverisfy();
numberOfNonImprovingItersCounter = 0;
}
var solutionPool = new List <Solution>();
solutionPool.AddRange(new CrossOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new TwoOptOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new ExchangeOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new RelocateOperator(currentSolution).GenerateFeasibleSolutions());
Solution candidateSolution = new Solution();
solutionPool = solutionPool.OrderBy(s => s.Cost).ToList();
for (var s = 0; s < solutionPool.Count; s++)
{
if (!tabuList.Contains(Helpers.GetStringFormOfSolution(solutionPool[s])))
{
candidateSolution = solutionPool[s];
break;
}
}
Console.WriteLine("Iteration: {0}, Time Elapsed: {1} sn, {2} candidate, Current Cost: {3}, Best Cost {4}",
i,
totalSecondsElapsed / 1_000.0,
solutionPool.Count,
Math.Round(currentSolution.Cost, 3),
Math.Round(_bestSolution.Cost, 3)
);
var currentCost = currentSolution.Cost;
var candidateCost = candidateSolution.Cost;
var acceptanceCondition = candidateCost < currentCost;
if (acceptanceCondition)
{
currentSolution = Helpers.Clone(candidateSolution);
if (currentSolution.Cost < _bestSolution.Cost)
{
_bestSolution = currentSolution;
}
}
else
{
numberOfNonImprovingItersCounter++;
}
tabuList.Enqueue(Helpers.GetStringFormOfSolution(candidateSolution));
}
stopwatch.Stop();
return(_bestSolution);
}
public Solution Run()
{
var stopwatch = new Stopwatch();
stopwatch.Restart();
var totalSecondsElapsed = 0.0;
var currentSolution = new LocalSearch(_dataset).Run();
var heuristicParams = Config.GetHeuristicsParam();
var iterationCount = heuristicParams.IterationCount;
var numberOfNonImprovingIters = heuristicParams.DiversificationParam.NumberOfNonImprovingIters;
var minCustomersToRemove = heuristicParams.DiversificationParam.MinCustomersToRemove;
var maxCustomersToRemove = heuristicParams.DiversificationParam.MaxCustomersToRemove;
var numberOfNonImprovingItersCounter = 0;
_bestSolution = currentSolution;
currentSolution = new Diversifier(Helpers.Clone(_bestSolution), minCustomersToRemove, maxCustomersToRemove).Diverisfy();
totalSecondsElapsed += TimeSpan.FromMilliseconds(stopwatch.ElapsedMilliseconds).TotalSeconds;
Console.WriteLine("Local search completed in {0} seconds!", Math.Round(totalSecondsElapsed, 3));
for (var i = 0; i <= iterationCount; i++)
{
stopwatch.Restart();
if (numberOfNonImprovingItersCounter == numberOfNonImprovingIters)
{
currentSolution = new Diversifier(Helpers.Clone(_bestSolution), minCustomersToRemove, maxCustomersToRemove).Diverisfy();
numberOfNonImprovingItersCounter = 0;
}
var solutionPool = new List <Solution>();
solutionPool.AddRange(new CrossOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new TwoOptOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new ExchangeOperator(currentSolution).GenerateFeasibleSolutions());
solutionPool.AddRange(new RelocateOperator(currentSolution).GenerateFeasibleSolutions());
var candidateSolution = Helpers.GetBestNeighbour(solutionPool);
var currentCost = currentSolution.Cost;
var candidateCost = candidateSolution.Cost;
var acceptanceCondition = candidateCost < currentCost;
if (acceptanceCondition)
{
currentSolution = Helpers.Clone(candidateSolution);
if (currentSolution.Cost < _bestSolution.Cost)
{
_bestSolution = currentSolution;
}
}
else
{
numberOfNonImprovingItersCounter++;
}
totalSecondsElapsed += TimeSpan.FromMilliseconds(stopwatch.ElapsedMilliseconds).TotalSeconds;
Console.WriteLine("Iteration: {0}, Time Elapsed: {1} sn, {2} candidate, Current Cost: {3}, Best Cost {4}",
i,
Math.Round(totalSecondsElapsed, 3),
solutionPool.Count,
Math.Round(currentSolution.Cost, 3),
Math.Round(_bestSolution.Cost, 3)
);
}
stopwatch.Stop();
return(_bestSolution);
}