diff --git a/algo/algo.go b/algo/algo.go
index 8602397..c271961 100644
--- a/algo/algo.go
+++ b/algo/algo.go
@@ -9,10 +9,10 @@ import (
 	"sort"
 	"sync"
 
-	"git.dotya.ml/wanderer/math-optim/algo/cec2020"
 	"git.dotya.ml/wanderer/math-optim/algo/de"
+	"git.dotya.ml/wanderer/math-optim/algo/ga"
 	"git.dotya.ml/wanderer/math-optim/bench"
-	c20 "git.dotya.ml/wanderer/math-optim/bench/cec2020"
+	"git.dotya.ml/wanderer/math-optim/bench/cec2020"
 	"git.dotya.ml/wanderer/math-optim/report"
 	"git.dotya.ml/wanderer/math-optim/stats"
 )
@@ -418,10 +418,8 @@ func DojDE(wg *sync.WaitGroup, m *sync.Mutex) {
 func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex) {
 	defer wg.Done()
 
-	cec2020.LogPrintln("starting")
-
 	// funcCount is the number of bench functions available and tested.
-	funcCount := len(c20.Functions)
+	funcCount := len(cec2020.Functions)
 	// stats for the current algo.
 	algoStats := make([][]stats.Stats, funcCount)
 	// ch serves as a way to get the actual computed output.
@@ -438,7 +436,7 @@ func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex) {
 	cr := 0.9
 
 	for i := range algoStats {
-		jDE := cec2020.NewjDE()
+		jDE := ga.NewjDE()
 
 		// params:
 		//  Generations, minimum bench iterations, mutation strategy, parameter
@@ -451,7 +449,7 @@ func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex) {
 		//  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, 30, 0, 0, np, f, cr, c20.Dimensions, c20.FuncNames[i], ch, chAlgoMeans)
+		jDE.Init(-1, 30, 0, 0, np, f, cr, cec2020.Dimensions, cec2020.FuncNames[i], ch, chAlgoMeans)
 
 		go jDE.Run()
 	}
@@ -466,8 +464,8 @@ func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex) {
 		saveAlgoMeans(*aM)
 	}
 
-	pCh := make(chan report.PicList, funcCount*len(c20.Dimensions))
-	pMeanCh := make(chan report.PicList, funcCount*len(c20.Dimensions))
+	pCh := make(chan report.PicList, funcCount*len(cec2020.Dimensions))
+	pMeanCh := make(chan report.PicList, funcCount*len(cec2020.Dimensions))
 
 	for _, algoStat := range algoStats {
 		go plotAllDims(algoStat, "plot", ".pdf", pCh, pMeanCh)