// Measure FPTAS time, average and max error
static (List <FPTASSummary>, string instanceResult) RunFPTAS(Dataset dataset, double[] errors)
{
Console.WriteLine("{0}: starting calculating dateset {1}", DateTime.Now, dataset.GetFilePath());
var csvBuilder = new StringBuilder();
csvBuilder.AppendLine(TestResultHelper.GetFPTASHeader());
List <FPTASResult> instacesResults = new List <FPTASResult>();
for (int i = 1; i <= dataset.LastInstanceId; i++)
{
Console.WriteLine($"{DateTime.Now}::{dataset.Name}::{dataset.InstanceItemsCount}::{i}");
// Load instance
var instance = InstanceLoader.LoadInstanceAsync(dataset, i);
if (instance == null)
{
continue;
}
// Load optimal soultion
int optimalResult = InstanceLoader.LoadSolution(dataset, i);
foreach (var err in errors)
{
instacesResults.Add(RunFPAS(instance, optimalResult, csvBuilder, err));
}
}
var summaryItems = new List <FPTASSummary>();
foreach (var err in errors)
{
summaryItems.Add(GetSummaryItem(dataset, instacesResults, err));
}
return(summaryItems, csvBuilder.ToString());
}
// Measure algorithms time
private static TestResult RunAlgorithms(Dataset dataSet, int measurementCount)
{
Console.WriteLine("{0}: starting calculating dateset {1}", DateTime.Now, dataSet.GetFilePath());
var csvBuilder = new StringBuilder();
csvBuilder.AppendLine(TestResultHelper.GetInstanceResultHeader());
var stopwatch = new Stopwatch();
double BFTotal = 0;
double BandBTotal = 0;
double dpTotal = 0;
double reduxTotal = 0;
double reduxErrSum = 0;
double reduxMaxErr = 0;
double greedyTotal = 0;
double greedyErrSum = 0;
double greedyMaxErr = 0;
double ftpasTotal = 0;
for (int i = 1; i <= dataSet.LastInstanceId; i++)
{
Console.WriteLine($"{DateTime.Now}::{dataSet.Name}::{dataSet.InstanceItemsCount}::{i}");
// Load instance and solution
var instance = InstanceLoader.LoadInstanceAsync(dataSet, i);
if (instance == null)
{
continue;
}
int optimalResult = InstanceLoader.LoadSolution(dataSet, i);
double bruteForceTimeAvg = 0;
double branchAndBoundTimeAvg = 0;
double dynamicProgrammingAvg = 0;
double greedyAvg = 0;
double reduxAvg = 0;
int[] greedyHeuristicResult = null;
int[] reduxHeuristicResult = null;
for (int j = 0; j < measurementCount; j++)
{
stopwatch.Reset();
// Start Brute Force
stopwatch.Start();
var bruteForceResult = BruteForce.Solve(0, instance.Weights, instance.Prices, 0, 0, instance.MaxWeight, instance.MinPrice, new int[instance.N + 1], new int[instance.N + 1]);
stopwatch.Stop();
CheckResult(instance, bruteForceResult[instance.N], optimalResult, dataSet.Name, nameof(BruteForce));
bruteForceTimeAvg += stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Reset();
// Start Branch and Bound
stopwatch.Start();
var branchAndBoundResult = BranchAndBound.Solve(0, instance.Weights, instance.Prices, 0, 0, instance.MaxWeight, new int[instance.N + 1], new int[instance.N + 1]);
//BranchAndBound.Decide(0, instance.Weights, instance.Prices, 0, 0, instance.MaxWeight, 324);
stopwatch.Stop();
CheckResult(instance, branchAndBoundResult[instance.N], optimalResult, dataSet.Name, nameof(BranchAndBound));
branchAndBoundTimeAvg += stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Reset();
// Start Dynamic programming
stopwatch.Start();
var dynamicProgrammingResult = DynamicProgramming.Solve(instance.Items, instance.MaxWeight);
stopwatch.Stop();
CheckResult(instance, dynamicProgrammingResult[instance.N], optimalResult, dataSet.Name, nameof(DynamicProgramming));
dynamicProgrammingAvg += stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Reset();
// Start Greedy heuristic
stopwatch.Start();
greedyHeuristicResult = GreedyHeuristic.Solve(instance.Items.ToList(), instance.MaxWeight);
stopwatch.Stop();
//CheckResult(instance, greedyHeuristicResult[instance.N], optimalPrice, dataSet.Name, nameof(GreedyHeuristic));
greedyAvg += stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Reset();
// Start Redux heuristic
stopwatch.Start();
reduxHeuristicResult = ReduxHeuristic.Solve(instance.Items.ToList(), instance.MaxWeight);
stopwatch.Stop();
reduxAvg += stopwatch.Elapsed.TotalMilliseconds;
stopwatch.Reset();
}
BFTotal += Avg(bruteForceTimeAvg, measurementCount);
BandBTotal += Avg(branchAndBoundTimeAvg, measurementCount);
dpTotal += Avg(dynamicProgrammingAvg, measurementCount);
greedyTotal += Avg(greedyAvg, measurementCount);
reduxTotal += Avg(reduxAvg, measurementCount);
csvBuilder.AppendLine(TestResultHelper.FormatInstanceResultRow(
instance.Id,
instance.N,
Avg(bruteForceTimeAvg, measurementCount),
Avg(branchAndBoundTimeAvg, measurementCount),
Avg(dynamicProgrammingAvg, measurementCount),
Avg(greedyAvg, measurementCount),
Avg(reduxAvg, measurementCount),
0
));
}
Console.WriteLine("{0}: calculating dataset {1} ended", DateTime.Now, dataSet.GetFilePath());
return(new TestResult
{
InstanceSize = dataSet.InstanceItemsCount,
InstancesResults = csvBuilder.ToString(),
BFTime = Avg(BFTotal, dataSet.InstancesCount),
BandBTime = Avg(BandBTotal, dataSet.InstancesCount),
GreedyHeuristicTime = Avg(greedyTotal, dataSet.InstancesCount),
ReduxHeuristicTime = Avg(reduxTotal, dataSet.InstancesCount),
DPTime = Avg(dpTotal, dataSet.InstancesCount),
FTPASTime = Avg(ftpasTotal, dataSet.InstancesCount),
GreedyRelErr = Avg(greedyErrSum, dataSet.InstancesCount),
GreedyMaxErr = greedyMaxErr,
ReduxRelErr = Avg(reduxErrSum, dataSet.InstancesCount),
ReduxMaxErr = reduxMaxErr
});
}
