private void Pick(decimal max, IKnapsackItem[] items, int index, KnapsackResult current)
{
if (current.Weight >= max)
{
return;
}
// picked weight > result and lower value than result.
if (index >= items.Length && current.Weight <= max)
{
if (current.Value > best.Value)
{
best = current.Clone() as KnapsackResult;
}
else if (current.Value == best.Value &&
current.Weight < best.Weight)
{
best = current.Clone() as KnapsackResult;
}
return;
}
//Pick
current.Items.Add(items[index]);
Pick(max, items, index + 1, current);
//Not pick
current.Items.Remove(items[index]);
Pick(max, items, index + 1, current);
}
public KnapsackResult Solve(KnapsackInstance instance)
{
BestConfiguration = new KnapsackConfiguration {
Price = 0, Weight = 0, ItemVector = new bool[instance.ItemCount].ToList()
};
FindBestConfiguration(0, new KnapsackConfiguration {
Price = 0, Weight = 0, ItemVector = new List <bool>()
}, instance.GetPriceOfAllItems(), instance);
var result = new KnapsackResult
{
KnapsackInstance = instance,
Configuration = BestConfiguration
};
return(result);
}
public IList <KnapsackResult> SolveWithPerformanceTest(IList <KnapsackInstance> instances, AnnealingOptions options)
{
PreparePerformanceTest(instances);
var stopWatch = new Stopwatch();
var results = new List <KnapsackResult>();
foreach (var instance in instances)
{
Console.WriteLine($"Processing instance no. {instance.Id}");
KnapsackResult result = null;
//The algorithm must run repeat at least the set amount of times;
for (int i = 0; i < REPEAT_COUNT; i++)
{
var solver = new SimulatedAnnealingSolver(instance, options);
GC.Collect();
GC.WaitForPendingFinalizers();
//GC.TryStartNoGCRegion(200000000);
stopWatch.Start();
result = solver.Solve();
stopWatch.Stop();
//GC.EndNoGCRegion();
}
var averageRuntime = stopWatch.Elapsed.TotalMilliseconds / REPEAT_COUNT;
//Save only the last result
if (result != null)
{
var optimalConfiguration = GetOptimalConfiguration(instance);
result.RunTimeMs = averageRuntime;
result.OptimalConfiguration = optimalConfiguration;
result.Epsilon = GetEpsilonOfSolution(result.Configuration.Price, optimalConfiguration.Price);
results.Add(result);
}
RaiseInstanceCalculationFinished();
stopWatch.Reset();
}
return(results);
}
public KnapsackResult Pick(decimal max, params IKnapsackItem[] items)
{
best = new KnapsackResult();
Pick(max, items, 0, new KnapsackResult());
return(best);
}
