func main() {
flag.Parse()
if flag.NArg() != 1 {
fmt.Println("Usage: go run samples/tsp.go ROUTEFILEPATH")
return
}
var routeFileName = flag.Arg(0)
if !File.Exists(routeFileName) {
fmt.Println("file " + routeFileName + " does not exist.")
return
}
fmt.Println("using route file: " + routeFileName)
idToPointLookup := readPoints(routeFileName)
fmt.Println("read " + strconv.Itoa(len(idToPointLookup)) + " points...")
calc := func(candidate string) int {
return getFitness(candidate, idToPointLookup)
}
if File.Exists(routeFileName + ".opt.tour") {
fmt.Println("found optimal solution file: " + routeFileName + ".opt")
optimalRoute := readOptimalRoute(routeFileName+".opt.tour", len(idToPointLookup))
fmt.Println("read " + strconv.Itoa(len(optimalRoute)) + " segments in the optimal route")
points := getPointsInOptimalOrder(idToPointLookup, optimalRoute)
genes := genericGeneSet[0:len(idToPointLookup)]
idToPointLookup = make(map[string]Point, len(idToPointLookup))
for i, v := range points {
idToPointLookup[genericGeneSet[i:i+1]] = v
}
fmt.Print("optimal route: " + genes)
fmt.Print("\t")
fmt.Println(getFitness(genes, idToPointLookup))
}
geneSet := genericGeneSet[0:len(idToPointLookup)]
start := time.Now()
disp := func(candidate string) {
fmt.Print(candidate)
fmt.Print("\t")
fmt.Print(getFitness(candidate, idToPointLookup))
fmt.Print("\t")
fmt.Println(time.Since(start))
}
var solver = new(genetic.Solver)
solver.MaxSecondsToRunWithoutImprovement = 20
solver.LowerFitnessesAreBetter = true
var best = solver.GetBest(calc, disp, geneSet, len(idToPointLookup), 1)
fmt.Println()
fmt.Println(best, "\t", getFitness(best, idToPointLookup))
fmt.Print("Total time: ")
fmt.Println(time.Since(start))
}
func main() {
flag.Parse()
if flag.NArg() != 1 {
fmt.Println("Usage: go run standard.go RESOURCEFILEPATH")
return
}
var resourceFileName = flag.Arg(0)
if !File.Exists(resourceFileName) {
fmt.Println("file " + resourceFileName + " does not exist.")
return
}
fmt.Println("using resource file: " + resourceFileName)
resources, maxWeight, solution := loadResources(resourceFileName)
optimalFitness := 0
for resource, count := range solution {
optimalFitness += resource.value * count
}
calc := func(candidate string) int {
decoded := decodeGenes(candidate, resources)
return getFitness(decoded, maxWeight, optimalFitness)
}
start := time.Now()
disp := func(candidate string) {
decoded := decodeGenes(candidate, resources)
fitness := getFitness(decoded, maxWeight, optimalFitness)
display(decoded, fitness, time.Since(start), true)
}
var solver = new(genetic.Solver)
solver.MaxSecondsToRunWithoutImprovement = 5
solver.MaxRoundsWithoutImprovement = 3
var best = solver.GetBestUsingHillClimbing(calc, disp, hexLookup, 10, numberOfGenesPerChromosome, optimalFitness)
fmt.Print("\nFinal: ")
decoded := decodeGenes(best, resources)
fitness := getFitness(decoded, maxWeight, optimalFitness)
display(decoded, fitness, time.Since(start), false)
if fitness == optimalFitness {
fmt.Println("-- that's the optimal solution!")
} else {
percentOptimal := float32(100) * float32(fitness) / float32(optimalFitness)
fmt.Printf("-- that's %f%% optimal\n", percentOptimal)
}
}