/** Start the background thread. */
public void start() {
// create a random list of cities
cities = new City[TravelingSalesman.CITY_COUNT];
for (int i = 0; i < TravelingSalesman.CITY_COUNT; i++) {
cities[i] =
new City(
(int) (Math.random() * (getBounds().width - 10)),
(int) (Math.random() * (getBounds().height - 60)));
}
// create the initial chromosomes
chromosomes = new Chromosome[TravelingSalesman.POPULATION_SIZE];
for (int i = 0; i < TravelingSalesman.POPULATION_SIZE; i++) {
chromosomes[i] = new Chromosome(cities);
chromosomes[i].setCut(cutLength);
chromosomes[i].setMutation(TravelingSalesman.MUTATION_PERCENT);
}
Chromosome.sortChromosomes(chromosomes, TravelingSalesman.POPULATION_SIZE);
// start up the background thread
started = true;
map.update(map.getGraphics());
generation = 0;
if (worker != null) worker = null;
worker = new Thread(this);
// worker.setPriority(Thread.MIN_PRIORITY);
worker.start();
}
public void run() {
Refs.setSim(this);
Refs.setCanvas(canvas);
Refs.setEnts(ents);
Refs.setMap(map);
// TODO TEMP
ents.add(new Creature());
//
long startTime = 0;
long endTime = 0;
long timeElapsed = 0;
int delay = 1000 / rate.getValue();
averageX = topQuarterX = 0;
smooth = false;
while (true) {
smooth = smoothMotion.isSelected();
startTime = System.currentTimeMillis();
canvas.repaint();
map.update();
ents.update();
if (ents.hasPopulationAbove(0)) {
averageX = ents.getAverageX();
topQuarterX = ents.getTopQuarterX();
}
endTime = System.currentTimeMillis();
timeElapsed = endTime - startTime;
delay = 1000 / rate.getValue();
Util.sleep(Util.trimInt((int) (delay - timeElapsed), 0, 99999999));
}
}
/** Start the background thread. */
public void start() {
// create a random list of cities
cities = new City[TravelingSalesman.CITY_COUNT];
for (int i = 0; i < TravelingSalesman.CITY_COUNT; i++) {
cities[i] =
new City(
(int) (Math.random() * (getBounds().width - 10)),
(int) (Math.random() * (getBounds().height - 60)));
}
// start up the background thread
started = true;
map.update(map.getGraphics());
if (worker != null) worker = null;
worker = new SimulateAnnealing(this);
worker.setPriority(Thread.MIN_PRIORITY);
worker.start();
}
@Override
public void update(float delta) {
if (!isGameOver) {
List<TouchEvent> events = stateManager.getTouchHandler().getTouchEvents();
if (!isExitDialogShowing) isExitDialogShowing = stateManager.isBackPressed();
if (isExitDialogShowing) {
events = yesButton.update(events);
events = noButton.update(events);
if (yesButton.state == Button.ACTIVATED) {
yesButton.disarm();
stateManager.setState(new MainMenuState(stateManager));
}
if (noButton.state == Button.ACTIVATED) {
noButton.disarm();
isExitDialogShowing = false;
}
} else {
if (switchTurns) {
if (map.getPlayer2() == map.getCurrentPlayersTurn()) events.clear();
events = switchTurnsOKButton.update(events);
events.clear();
if (switchTurnsOKButton.state == Button.ACTIVATED) {
switchTurnsOKButton.disarm();
switchTurns = false;
checkWin = true;
map.doneSwitchingTurns();
}
}
map.update(events);
}
} else {
// TODO: maybe take us to a game breakdown state which records stats for the match
// right now, just take us back to the main menu
stateManager.setState(new MainMenuState(stateManager));
}
}
public static void main(String[] args) throws IOException {
Map map = Parser.readMap("example1.map");
Robot r = new Robot(map, Parser.posX, Parser.posY);
map.printMap();
saveState(map, r);
while (!r.isOver && !map.killedRobot) {
int type = getInput(r);
if (type == 0) {
map.update();
map.printMap();
play++;
saveState(map, r);
}
if (type == 1) {
undo();
}
}
}
/** The main loop for the background thread. It is here that most of the work os orchestrated. */
public void run() {
double thisCost = 500.0;
double oldCost = 0.0;
double dcost = 500.0;
int countSame = 0;
map.update(map.getGraphics());
while (countSame < 100) {
generation++;
int ioffset = matingPopulationSize;
int mutated = 0;
// Mate the chromosomes in the favoured population
// with all in the mating population
for (int i = 0; i < favoredPopulationSize; i++) {
Chromosome cmother = chromosomes[i];
// Select partner from the mating population
int father = (int) (0.999999 * Math.random() * (double) matingPopulationSize);
Chromosome cfather = chromosomes[father];
mutated += cmother.mate(cfather, chromosomes[ioffset], chromosomes[ioffset + 1]);
ioffset += 2;
}
// The new generation is in the matingPopulation area
// move them to the correct area for sort.
for (int i = 0; i < matingPopulationSize; i++) {
chromosomes[i] = chromosomes[i + matingPopulationSize];
chromosomes[i].calculateCost(cities);
}
// Now sort the new mating population
Chromosome.sortChromosomes(chromosomes, matingPopulationSize);
double cost = chromosomes[0].getCost();
dcost = Math.abs(cost - thisCost);
thisCost = cost;
double mutationRate = 100.0 * (double) mutated / (double) matingPopulationSize;
NumberFormat nf = NumberFormat.getInstance();
nf.setMinimumFractionDigits(2);
nf.setMinimumFractionDigits(2);
status.setText(
"Generation "
+ generation
+ " Cost "
+ (int) thisCost
+ " Mutated "
+ nf.format(mutationRate)
+ "%");
if ((int) thisCost == (int) oldCost) {
countSame++;
} else {
countSame = 0;
oldCost = thisCost;
}
map.update(map.getGraphics());
}
status.setText("Solution found after " + generation + " generations.");
}
public void paint() {
map.update(getGraphics());
}
