go(de): add benchMinIters param

algo/algo.go

@@ -350,15 +350,17 @@ funcCount := len(bench.Functions)
 		jDE := de.NewjDE()
 
 		// params:
-		//  Generations, mutation strategy, parameter self-adaptation scheme,
-		//  initial population size, differential weight, mutation constant,
-		//  dimensions, bench name and a synchronisation channel.
+		//  Generations, minimum bench iterations, mutation strategy, parameter
+		//  self-adaptation scheme, initial population size, differential
+		//  weight, mutation constant, dimensions, bench name and a
+		//  synchronisation channel.
 		//
 		//  -1 to disable generation limits,
+		//  n > 0 for minimum bench iterations
 		//  0..17 to choose a mutation strategy,
 		//  0..1 to select a parameter self-adaptation scheme,
 		//  np >= 4 as initial population size.
-		jDE.Init(-1, 0, 0, np, f, cr, bench.DimensionsGA, bench.FuncNames[i], ch)
+		jDE.Init(-1, 30, 0, 0, np, f, cr, bench.DimensionsGA, bench.FuncNames[i], ch)
 
 		go jDE.Run()
 	}

algo/de/jDE.go

@@ -17,6 +17,8 @@ type JDE struct {
 	// Generations denotes the number of generations the population evolves
 	// for. Special value -1 disables limiting the number of generations.
 	Generations int
+	// BenchMinIters is the number of iterations the bench function will be re-run (for statistical purposes).
+	BenchMinIters int
 	// Dimensions to solve the problem for.
 	Dimensions []int
 	// F is the differential weight (mutation/weighting factor).
@@ -61,7 +63,7 @@ type JDE struct {
 var jDELogger = log.New(os.Stderr, " *** δ jDE:", log.Ldate|log.Ltime|log.Lshortfile)
 
 // Init initialises the jDE algorithm, performs sanity checks on the inputs.
-func (j *JDE) Init(generations, mutStrategy, adptScheme, np int, f, cr float64, dimensions []int, bench string, ch chan []stats.Stats) {
+func (j *JDE) Init(generations, benchMinIters, mutStrategy, adptScheme, np int, f, cr float64, dimensions []int, bench string, ch chan []stats.Stats) {
 	if j == nil {
 		jDELogger.Fatalln("jDE needs to be initialised before calling RunjDE, exiting...")
 	}
@@ -74,6 +76,9 @@ func (j *JDE) Init(generations, mutStrategy, adptScheme, np int, f, cr float64,
 	case generations == -1:
 		jDELogger.Println("Generations is '-1', disabling generation limits..")
 
+	case benchMinIters < 1:
+		jDELogger.Fatalln("Minimum bench iterations cannot be less than 1, got:", benchMinIters)
+
 	case mutStrategy < 0 || mutStrategy > 17:
 		jDELogger.Fatalln("Mutation strategy needs to be from the interval <0; 17>, got", mutStrategy)
 
@@ -97,6 +102,7 @@ func (j *JDE) Init(generations, mutStrategy, adptScheme, np int, f, cr float64,
 	}
 
 	j.Generations = generations
+	j.BenchMinIters = benchMinIters
 	j.MutationStrategy = mutStrategy
 	j.AdptScheme = adptScheme
 	j.NP = np
@@ -128,12 +134,12 @@ func (j *JDE) Init(generations, mutStrategy, adptScheme, np int, f, cr float64,
 
 // InitAndRun initialises the jDE algorithm, performs sanity checks on the
 // inputs and calls the Run method.
-func (j *JDE) InitAndRun(generations, mutStrategy, adptScheme, np int, f, cr float64, dimensions []int, bench string, ch chan []stats.Stats) {
+func (j *JDE) InitAndRun(generations, benchMinIters, mutStrategy, adptScheme, np int, f, cr float64, dimensions []int, bench string, ch chan []stats.Stats) {
 	if j == nil {
 		jDELogger.Fatalln("jDE is nil, NewjDE() needs to be called first. exiting...")
 	}
 
-	j.Init(generations, mutStrategy, adptScheme, np, f, cr, dimensions, bench, ch)
+	j.Init(generations, benchMinIters, mutStrategy, adptScheme, np, f, cr, dimensions, bench, ch)
 
 	j.Run()
 }