- Timestamp:
- 02/17/17 13:01:00 (8 years ago)
- Location:
- branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3
- Files:
-
- 2 edited
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branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3
- Property svn:ignore
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old new 9 9 GeneratedArtifacts 10 10 _Pvt_Extensions 11 *.DotSettings
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- Property svn:ignore
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branches/MemPRAlgorithm/HeuristicLab.Algorithms.MemPR/3.3/MemPRContext.cs
r14573 r14680 346 346 #region Breeding Performance 347 347 public void AddBreedingResult(ISingleObjectiveSolutionScope<TSolution> a, ISingleObjectiveSolutionScope<TSolution> b, double parentDist, ISingleObjectiveSolutionScope<TSolution> child) { 348 return; 348 349 if (IsBetter(a, b)) 349 350 breedingStat.Add(Tuple.Create(a.Fitness, b.Fitness, parentDist, child.Fitness)); … … 352 353 } 353 354 public void RelearnBreedingPerformanceModel() { 355 return; 354 356 breedingPerformanceModel = RunRegression(PrepareRegression(ToListRow(breedingStat)), breedingPerformanceModel).Model; 355 357 } 356 358 public bool BreedingSuited(ISingleObjectiveSolutionScope<TSolution> p1, ISingleObjectiveSolutionScope<TSolution> p2, double dist) { 359 return true; 357 360 if (breedingPerformanceModel == null) return true; 358 361 double minI1 = double.MaxValue, minI2 = double.MaxValue, maxI1 = double.MinValue, maxI2 = double.MinValue; … … 372 375 #region Relinking Performance 373 376 public void AddRelinkingResult(ISingleObjectiveSolutionScope<TSolution> a, ISingleObjectiveSolutionScope<TSolution> b, double parentDist, ISingleObjectiveSolutionScope<TSolution> child) { 377 return; 374 378 if (IsBetter(a, b)) 375 379 relinkingStat.Add(Tuple.Create(a.Fitness, b.Fitness, parentDist, Maximization ? child.Fitness - a.Fitness : a.Fitness - child.Fitness)); … … 378 382 } 379 383 public void RelearnRelinkingPerformanceModel() { 384 return; 380 385 relinkingPerformanceModel = RunRegression(PrepareRegression(ToListRow(relinkingStat)), relinkingPerformanceModel).Model; 381 386 } 382 387 public bool RelinkSuited(ISingleObjectiveSolutionScope<TSolution> p1, ISingleObjectiveSolutionScope<TSolution> p2, double dist) { 388 return true; 383 389 if (relinkingPerformanceModel == null) return true; 384 390 double minI1 = double.MaxValue, minI2 = double.MaxValue, maxI1 = double.MinValue, maxI2 = double.MinValue; … … 401 407 #region Delinking Performance 402 408 public void AddDelinkingResult(ISingleObjectiveSolutionScope<TSolution> a, ISingleObjectiveSolutionScope<TSolution> b, double parentDist, ISingleObjectiveSolutionScope<TSolution> child) { 409 return; 403 410 if (IsBetter(a, b)) 404 411 delinkingStat.Add(Tuple.Create(a.Fitness, b.Fitness, parentDist, Maximization ? child.Fitness - a.Fitness : a.Fitness - child.Fitness)); … … 407 414 } 408 415 public void RelearnDelinkingPerformanceModel() { 416 return; 409 417 delinkingPerformanceModel = RunRegression(PrepareRegression(ToListRow(delinkingStat)), delinkingPerformanceModel).Model; 410 418 } 411 419 public bool DelinkSuited(ISingleObjectiveSolutionScope<TSolution> p1, ISingleObjectiveSolutionScope<TSolution> p2, double dist) { 420 return true; 412 421 if (delinkingPerformanceModel == null) return true; 413 422 double minI1 = double.MaxValue, minI2 = double.MaxValue, maxI1 = double.MinValue, maxI2 = double.MinValue; … … 429 438 #region Sampling Performance 430 439 public void AddSamplingResult(ISingleObjectiveSolutionScope<TSolution> sample, double avgDist) { 440 return; 431 441 samplingStat.Add(Tuple.Create(avgDist, sample.Fitness)); 432 442 if (samplingStat.Count % 10 == 0) RelearnSamplingPerformanceModel(); 433 443 } 434 444 public void RelearnSamplingPerformanceModel() { 445 return; 435 446 samplingPerformanceModel = RunRegression(PrepareRegression(ToListRow(samplingStat)), samplingPerformanceModel).Model; 436 447 } 437 448 public bool SamplingSuited(double avgDist) { 449 return true; 438 450 if (samplingPerformanceModel == null) return true; 439 451 if (avgDist < samplingStat.Min(x => x.Item1) || avgDist > samplingStat.Max(x => x.Item1)) return true; … … 444 456 #region Hillclimbing Performance 445 457 public void AddHillclimbingResult(ISingleObjectiveSolutionScope<TSolution> input, ISingleObjectiveSolutionScope<TSolution> outcome) { 458 return; 446 459 hillclimbingStat.Add(Tuple.Create(input.Fitness, Maximization ? outcome.Fitness - input.Fitness : input.Fitness - outcome.Fitness)); 447 460 if (hillclimbingStat.Count % 10 == 0) RelearnHillclimbingPerformanceModel(); 448 461 } 449 462 public void RelearnHillclimbingPerformanceModel() { 463 return; 450 464 hillclimbingPerformanceModel = RunRegression(PrepareRegression(ToListRow(hillclimbingStat)), hillclimbingPerformanceModel).Model; 451 465 } 452 466 public bool HillclimbingSuited(double startingFitness) { 467 return true; 453 468 if (hillclimbingPerformanceModel == null) return true; 454 469 if (startingFitness < HillclimbingStat.Min(x => x.Item1) || startingFitness > HillclimbingStat.Max(x => x.Item1)) … … 460 475 #region Adaptivewalking Performance 461 476 public void AddAdaptivewalkingResult(ISingleObjectiveSolutionScope<TSolution> input, ISingleObjectiveSolutionScope<TSolution> outcome) { 477 return; 462 478 adaptivewalkingStat.Add(Tuple.Create(input.Fitness, Maximization ? outcome.Fitness - input.Fitness : input.Fitness - outcome.Fitness)); 463 479 if (adaptivewalkingStat.Count % 10 == 0) RelearnAdaptiveWalkPerformanceModel(); 464 480 } 465 481 public void RelearnAdaptiveWalkPerformanceModel() { 482 return; 466 483 adaptiveWalkPerformanceModel = RunRegression(PrepareRegression(ToListRow(adaptivewalkingStat)), adaptiveWalkPerformanceModel).Model; 467 484 } 468 485 public bool AdaptivewalkingSuited(double startingFitness) { 486 return true; 469 487 if (adaptiveWalkPerformanceModel == null) return true; 470 488 if (startingFitness < AdaptivewalkingStat.Min(x => x.Item1) || startingFitness > AdaptivewalkingStat.Max(x => x.Item1))
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