We Keep Coding

Java MultiThreading not stopping

I have the following code for a kind of 'stopwatch' that extends the Thread class:
package StopWatch;
//Code taken from:
//https://stackoverflow.com/questions/9526041/how-to-program-for-a-stopwatch
public class Stopwatch extends Thread {
private long startTime;
private boolean started;
public void startTimer() {
this.startTime = System.currentTimeMillis();
this.started = true;
this.start();
}
public void run() {
while(started){/*currentTimeMillis increases on its own */}
System.out.println("timer stopped");
}
public int[] getTime() {
long milliTime = System.currentTimeMillis() - this.startTime;
int[] time = new int[]{0,0,0,0};
time[0] = (int)(milliTime / 3600000); //gives number of hours elapsed
time[1] = (int)(milliTime / 60000) % 60; //gives number of remaining minutes elapsed
time[2] = (int)(milliTime / 1000) % 60; //gives number of remaining seconds elapsed
time[3] = (int)(milliTime); //gives number of remaining milliseconds elapsed
return time;
}
public void stopTimer() {
this.started = false;
}
}
and I'm testing it in the following driver class:
import StopWatch.Stopwatch;
public class StopWatchTest {
public static void main(String[] args) {
Stopwatch stopwatch = new Stopwatch();
stopwatch.startTimer();
int sum = 0;
for (long i = 0; i < 100000; i++) {
sum++;
}
int[] time = stopwatch.getTime();
for (int i = 0; i < 4; i++) {
if (i < 3) {
System.out.print(time[i]+":");
} else {
System.out.print(time[i]);
}
}
stopwatch.stopTimer();
}
}
My intent is to use instances of class Stopwatch to measure the performance of various blocks of code (The for-loop in the driver class for instance) by having these Stopwatch objects in a main thread start a timer in separate thread before executing the blocks of code I want to evaluate, then have them (the Stopwatch objects) stop their timer once execution of said blocks in the main thread have finished. I understand that there are much simpler and easier ways to do this but I wanted to try doing it this way as sort of a "proof of concept" and to simply get better with multi-threading, but I'm encountering some problems:
1) When I run the driver class StopWatchTest I get seemingly random and arbitrary output each time (but mostly 0:0:0:0)
2) The main thread (or possibly the Stopwatch thread, I'm not even sure anymore) seems to never stop executing after I get outputs like 0:0:0:0
3) When I try debugging with breakpoints and the like I get completely unexpected behavior depending on where I put the breakpoints (The main thread does sometime finish execution but with random outputs like 0:0:13:2112 and other times I just get stuck in the Stopwatch thread)
Point 3 doesn't concern me as much as 1 and 2 as I have limited knowledge of how multi-threading behaves when one or several of the threads are paused at breakpoints for debugging (I suspect that when I break in the main thread the Stopwatch thread continues running). Points 1 and 2 bother me much more as I cannot see why they would be occurring.

To get you started, you should flag the boolean started as volatile:
private volatile boolean started;
That should work, but it would make a busy loop, which is very bad for your CPU usage.
You should look to wait()/notify() methods next.

Java factorial calculation with thread pool

I achieved to calculate factorial with two threads without the pool. I have two factorial classes which are named Factorial1, Factorial2 and extends Thread class. Let's consider I want to calculate the value of !160000. In Factorial1's run() method I do the multiplication in a for loop from i=2 to i=80000 and in Factorial2's from i=80001 to 160000. After that, i return both values and multiply them in the main method. When I compare the execution time it's much better (which is 5000 milliseconds) than the non-thread calculation's time (15000 milliseconds) even with two threads.
Now I want to write clean and better code because I saw the efficiency of threads at factorial calculation but when I use a thread pool to calculate the factorial value, the parallel calculation always takes more time than the non-thread calculation (nearly 16000). My code pieces look like:
for(int i=2; i<= Calculate; i++)
{
myPool.execute(new Multiplication(result, i));
}
run() method which is in Multiplication class:
public void run()
{
s1.Mltply(s2); // s1 and s2 are instances of my Number class
// their fields holds BigInteger values
}
Mltply() method which is in Number class:
public void Multiply(int number)
{
area.lock(); // result is going wrong without lock
Number temp = new Number(number);
value = value.multiply(temp.value); // value is a BigInteger
area.unlock();
}
In my opinion this lock may kills the all advantage of the thread usage because it seems like all that threads do is multiplication but nothing else. But without it, i can't even calculate the true result. Let's say i want to calculate !10, so thread1 calculates the 10*9*8*7*6 and thread2 calculate the 5*4*3*2*1. Is that the way I'm looking for? Is it even possible with thread pool? Of course execution time must be less than the normal calculation...
I appreciate all your help and suggestion.
EDIT: - My own solution to the problem -
public class MyMultiplication implements Runnable
{
public static BigInteger subResult1;
public static BigInteger subResult2;
int thread1StopsAt;
int thread2StopsAt;
long threadId;
static boolean idIsSet=false;
public MyMultiplication(BigInteger n1, int n2) // First Thread
{
MyMultiplication.subResult1 = n1;
this.thread1StopsAt = n2/2;
thread2StopsAt = n2;
}
public MyMultiplication(int n2,BigInteger n1) // Second Thread
{
MyMultiplication.subResult2 = n1;
this.thread2StopsAt = n2;
thread1StopsAt = n2/2;
}
#Override
public void run()
{
if(idIsSet==false)
{
threadId = Thread.currentThread().getId();
idIsSet=true;
}
if(Thread.currentThread().getId() == threadId)
{
for(int i=2; i<=thread1StopsAt; i++)
{
subResult1 = subResult1.multiply(BigInteger.valueOf(i));
}
}
else
{
for(int i=thread1StopsAt+1; i<= thread2StopsAt; i++)
{
subResult2 = subResult2.multiply(BigInteger.valueOf(i));
}
}
}
}
public class JavaApplication3
{
public static void main(String[] args) throws InterruptedException
{
int calculate=160000;
long start = System.nanoTime();
BigInteger num = BigInteger.valueOf(1);
for (int i = 2; i <= calculate; i++)
{
num = num.multiply(BigInteger.valueOf(i));
}
long end = System.nanoTime();
double time = (end-start)/1000000.0;
System.out.println("Without threads: \t" +
String.format("%.2f",time) + " miliseconds");
System.out.println("without threads Result: " + num);
BigInteger num1 = BigInteger.valueOf(1);
BigInteger num2 = BigInteger.valueOf(1);
ExecutorService myPool = Executors.newFixedThreadPool(2);
start = System.nanoTime();
myPool.execute(new MyMultiplication(num1,calculate));
Thread.sleep(100);
myPool.execute(new MyMultiplication(calculate,num2));
myPool.shutdown();
while(!myPool.isTerminated()) {} // waiting threads to end
end = System.nanoTime();
time = (end-start)/1000000.0;
System.out.println("With threads: \t" +String.format("%.2f",time)
+ " miliseconds");
BigInteger result =
MyMultiplication.subResult1.
multiply(MyMultiplication.subResult2);
System.out.println("With threads Result: " + result);
System.out.println(MyMultiplication.subResult1);
System.out.println(MyMultiplication.subResult2);
}
}
input : !160000
Execution time without threads : 15000 milliseconds
Execution time with 2 threads : 4500 milliseconds
Thanks for ideas and suggestions.

You may calculate !160000 concurrently without using a lock by splitting 160000 into disjunct junks as you explaint by splitting it into 2..80000 and 80001..160000.
But you may achieve this by using the Java Stream API:
IntStream.rangeClosed(1, 160000).parallel()
.mapToObj(val -> BigInteger.valueOf(val))
.reduce(BigInteger.ONE, BigInteger::multiply);
It does exactly what you try to do. It splits the whole range into junks, establishes a thread pool and computes the partial results. Afterwards it joins the partial results into a single result.
So why do you bother doing it by yourself? Just practicing clean coding?
On my real 4 core machine computation in a for loop took 8 times longer than using a parallel stream.

Threads have to run independent to run fast. Many dependencies like locks, synchronized parts of your code or some system calls leads to sleeping threads which are waiting to access some resources.
In your case you should minimize the time a thread is inside the lock. Maybe I am wrong, but it seems like you create a thread for each number. So for 1.000! you spawn 1.000 Threads. All of them trying to get the lock on area and are not able to calculate anything, because one thread has become the lock and all other threads have to wait until the lock is unlocked again. So the threads are only running in serial which is as fast as your non-threaded example plus the extra time for locking and unlocking, thread management and so on. Oh, and because of cpu's context switching it gets even worse.
Your first attempt to splitt the factorial in two threads is the better one. Each thread can calculate its own result and only when they are done the threads have to communicate with each other. So they are independent most of the time.
Now you have to generalize this solution. To reduce context switching of the cpu you only want as many threads as your cpu has cores (maybe a little bit less because of your OS). Every thread gets a rang of numbers and calculates their product. After this it locks the overall result and adds its own result to it.
This should improve the performance of your problem.
Update: You ask for additional advice:
You said you have two classes Factorial1 and Factorial2. Probably they have their ranges hard codes. You only need one class which takes the range as constructor arguments. This class implements Runnable so it has a run-Method which multiplies all values in that range.
In you main-method you can do something like that:
int n = 160_000;
int threads = 2;
ExecutorService executor = Executors.newFixedThreadPool(threads);
for (int i = 0; i < threads; i++) {
int start = i * (n/threads) + 1;
int end = (i + 1) * (n/threads) + 1;
executor.execute(new Factorial(start, end));
}
executor.shutdown();
executor.awaitTermination(1, TimeUnit.DAYS);
Now you have calculated the result of each thread but not the overall result. This can be solved by a BigInteger which is visible to the Factorial-class (like a static BigInteger reuslt; in the same main class.) and a lock, too. In the run-method of Factorial you can calculate the overall result by locking the lock and calculation the result:
Main.lock.lock();
Main.result = Main.result.multiply(value);
Main.lock.unlock();
Some additional advice for the future: This isn't really clean because Factorial needs to have information about your main class, so it has a dependency to it. But ExecutorService returns a Future<T>-Object which can be used to receive the result of the thread. Using this Future-Object you don't need to use locks. But this needs some extra work, so just try to get this running for now ;-)

In addition to my Java Stream API solution here another solution which uses a self-managed thread-pool as you demanded:
public static final int CHUNK_SIZE = 10000;
public static BigInteger fac(int max) {
ExecutorService executor = newCachedThreadPool();
try {
return rangeClosed(0, (max - 1) / CHUNK_SIZE)
.mapToObj(val -> executor.submit(() -> prod(leftBound(val), rightBound(val, max))))
.map(future -> valueOf(future))
.reduce(BigInteger.ONE, BigInteger::multiply);
} finally {
executor.shutdown();
}
}
private static int leftBound(int chunkNo) {
return chunkNo * CHUNK_SIZE + 1;
}
private static int rightBound(int chunkNo, int max) {
return Math.min((chunkNo + 1) * CHUNK_SIZE, max);
}
private static BigInteger valueOf(Future<BigInteger> future) {
try {
return future.get();
} catch (Exception e) {
throw new RuntimeException(e);
}
}
private static BigInteger prod(int min, int max) {
BigInteger res = BigInteger.valueOf(min);
for (int val = min + 1; val <= max; val++) {
res = res.multiply(BigInteger.valueOf(val));
}
return res;
}

Why does my Java program's performance drop significantly after startup?

I am writing a small Java application to analyze a large number of image files. For now, it finds the brightest image in a folder by averaging the brightness of every pixel in the image and comparing it to the other images in the folder.
Sometimes, I get a rate of 100+ images/second right after startup, but this almost always drops to < 20 images/second, and I'm not sure why. When it is at 100+ images/sec, the CPU usage is 100%, but then it drops to around 20%, which seems too low.
Here's the main class:
public class ImageAnalysis {
public static final ConcurrentLinkedQueue<File> queue = new ConcurrentLinkedQueue<>();
private static final ConcurrentLinkedQueue<ImageResult> results = new ConcurrentLinkedQueue<>();
private static int size;
private static AtomicInteger running = new AtomicInteger();
private static AtomicInteger completed = new AtomicInteger();
private static long lastPrint = 0;
private static int completedAtLastPrint;
public static void main(String[] args){
File rio = new File(IO.CAPTURES_DIRECTORY.getAbsolutePath() + File.separator + "Rio de Janeiro");
String month = "12";
Collections.addAll(queue, rio.listFiles((dir, name) -> {
return (name.substring(0, 2).equals(month));
}));
size = queue.size();
ExecutorService executor = Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors() + 1);
for (int i = 0; i < 8; i++){
AnalysisThread t = new AnalysisThread();
t.setPriority(Thread.MAX_PRIORITY);
executor.execute(t);
running.incrementAndGet();
}
}
public synchronized static void finished(){
if (running.decrementAndGet() <= 0){
ImageResult max = new ImageResult(null, 0);
for (ImageResult r : results){
if (r.averageBrightness > max.averageBrightness){
max = r;
}
}
System.out.println("Max Red: " + max.averageBrightness + " File: " + max.file.getAbsolutePath());
}
}
public synchronized static void finishedImage(ImageResult result){
results.add(result);
int c = completed.incrementAndGet();
if (System.currentTimeMillis() - lastPrint > 10000){
System.out.println("Completed: " + c + " / " + size + " = " + ((double) c / (double) size) * 100 + "%");
System.out.println("Rate: " + ((double) c - (double) completedAtLastPrint) / 10D + " images / sec");
completedAtLastPrint = c;
lastPrint = System.currentTimeMillis();
}
}
}
And the thread class:
public class AnalysisThread extends Thread {
#Override
public void run() {
while(!ImageAnalysis.queue.isEmpty()) {
File f = ImageAnalysis.queue.poll();
BufferedImage image;
try {
image = ImageIO.read(f);
double color = 0;
for (int x = 0; x < image.getWidth(); x++) {
for (int y = 0; y < image.getHeight(); y++) {
//Color c = new Color(image.getRGB(x, y));
color += image.getRGB(x,y);
}
}
color /= (image.getWidth() * image.getHeight());
ImageAnalysis.finishedImage((new ImageResult(f, color)));
} catch (IOException e) {
e.printStackTrace();
}
}
ImageAnalysis.finished();
}
}

You appear to have a mixed up both using a thread pool and creating threads of your own. I suggest you use on or the other. In fact I suggest you only use the fixed thread pool
Most likely what is happening is your threads are getting an exception which is being lost but killing the task which kills the thread.
I suggest you just the the thread pool, don't attempt to create your own threads, or queue as this is that the ExecutorService does for you. For each task, submit it to the pool, one per image and if you are not going to check the Error of any task, I suggest you trap all Throwable and log them otherwise you could get a RuntimeExcepion or Error and have no idea this happened.
If you have Java 8, a simpler approach would be to use parallelStream(). You can use this to analyse the images concurrently and collect the results without having to divide up the work and collect the results. e.g
List<ImageResults> results = Stream.of(rio.listFiles())
.parallel()
.filter(f -> checkFile(f))
.map(f -> getResultsFor(f))
.list(Collectors.toList());

I see two reasons why you may experience CPU usage deterioration:
your tasks are very I/O intensive (reading images - ImageIO.read(f));
there is thread contention over the synchronized method that your threads access;
Further the sizes of the images may influence execution times.
To exploit parallelism efficiently I would suggest that you redesign your app and implement two kind of tasks that would be submitted to the executor:
the first tasks (producers) would be I/O intensive and will read the image data and queue it for in-memory processing;
the other (consumers) will pull and analyze the image information;
Then with some profiling you will be able to determine the correct ratio between producers and consumers.

The problem I could see here is the usage of queues in the high-performance concurrency model you are looking for. Using a queue is not optimal while using with a modern CPU design. Queue implementations have write contention on the head, tail and size variables. They are either always close to full or close to empty due to differences in pace between consumers and producers, especially while using in a high I/O situation. This results in high levels of contention. Further, in Java queues are significant source of garbage.
What I suggest is to apply Mechanical Sympathy while designing your code. One of the best solution you can have is the usage of LMAX Disruptor, which is a high performance inter-thread messaging library, which is aimed to solve this concurrency problem
Additional References
http://lmax-exchange.github.io/disruptor/files/Disruptor-1.0.pdf
http://martinfowler.com/articles/lmax.html
https://dzone.com/articles/mechanical-sympathy
http://www.infoq.com/presentations/mechanical-sympathy

Java Executor that adjusts thread pool based on CPU and RAM usage

My application uses an Executor to provide a thread pool for a large number of tasks. I've determined, through both analysis and benchmarking, that my application runs fastest when there are multiple threads per core. A good heuristic is start with 4 threads per core, varying until you hit >90% CPU or >90% RAM.
Is there an Executor available that will do this out of the box? Either automatically use N threads per core (not just one), or, ideally, throttle the thread pool size based on CPU and RAM usage?
Failing that - How can I determine the number of cores programatically?

One approach would be to use a ThreadPoolExecutor with a core size of 1, a starting maximum pool size of 4, then adjust the maximum pool size dynamically, based on memory and CPU usage.
The bigger problem, imho, is how to measure memory usage and CPU load. The memory usage is easy enough:
public double memUsageRatio() {
Runtime r = Runtime.getRuntime();
return (double) (r.totalMemory() - r.freeMemory()) / r.maxMemory();
}
For the CPU load, it can be more problematic, depending on the platform you run on. On Linux, you can use:
ManagementFactory.getOperatingSystemMXBean().getSystemLoadAverage();
This returns the system load average for the last minute. Unfortunately, on Windows this method always returns -1. In the past, I have replaced it with an approximation of the system load average for a given interval, by computing the sum of the CPU times for all the threads, divided by the sum of all elapsed times for all processors. This is only an approximation, but it works pretty good in most cases:
import java.lang.management.*;
public class CPUUsageCollector implements Runnable {
private final static long INTERVAL = 1000L; // polling interval in ms
private long totalCpuTime = 0L; // total CPU time in millis
private double load = 0d; // average load over the interval
ThreadMXBean threadMXBean = ManagementFactory.getThreadMXBean();
boolean stopped = false;
#Override
public void run() {
try {
while (!isStopped()) {
long start = System.currentTimeMillis();
long[] ids = threadMXBean.getAllThreadIds();
long time = 0L;
for (long id: ids) {
long l = threadMXBean.getThreadCpuTime(id);
if (l >= 0L) time += l;
}
long newCpuTime = time / 1000000L;
synchronized(this) {
long oldCpuTime = totalCpuTime;
totalCpuTime = newCpuTime;
// load = CPU time difference / sum of elapsed time for all CPUs
load = (double) (newCpuTime - oldCpuTime) /
(double) (INTERVAL * Runtime.getRuntime().availableProcessors());
}
long sleepTime = INTERVAL - (System.currentTimeMillis() - start);
goToSleep(sleepTime <= 0L ? INTERVAL : sleepTime);
}
} catch (Exception e) {
e.printStackTrace();
}
}
public synchronized double getLoad() {
return load;
}
public synchronized void goToSleep(final long time) {
try {
wait(time);
} catch(InterruptedException e) {
e.printStackTrace();
}
}
public synchronized boolean isStopped() {
return stopped;
}
public synchronized void setStopped(final boolean stopped) {
this.stopped = stopped;
}
}

Runtime.availableProcessors()
Javadoc:
Returns the number of processors available to the Java virtual machine.
This value may change during a particular invocation of the virtual machine. Applications that are sensitive to the number of available processors should therefore occasionally poll this property and adjust their resource usage appropriately.

How to run a Thread for a user specified amount of time?

Am creating a program that is based on mixing and making perturbation in a population containing solutions Vector.
So I created a for loop that stops after a certain time given by the user.
Inside the loop, am going to call 5 procedures and I thought that if i put each procedure in a thread will make the program making more solutions in a same time than calling normal methods.
Here 5 created the 5 threads, but when i start them the don't want to stop even if i use the Thread.stop, Thread.suspend, Thread.interrupt or Thread.destroy
Here is my code and could u help me with your ideas ?
I have inserted a new variable :
public volatile boolean CrossOpb = true;`
Here is my code:
Thread CrossOp = new Thread(new Runnable() {
public void run() {
while(CrossOpb == true){
int rdmCross2=(int) (Math.random() * allPopulation.size()) ; // Crossover 1st vector
int rdmCross1=(int) (Math.random() * allPopulation.size()) ;
Vector muted = new Vector();
Vector copy = copi((Vector) allPopulation.get(rdmCross2));
Vector callp = copi((Vector) allPopulation.get(rdmCross1));
muted = crossover(callp, copy);
System.out.println("cross over Between two Randoms ----------->");
affiche_resultat(muted);
allPopulation.add(muted);
}
}
});
The loop :
CrossOp.setDaemon(true);
int loop = 1;
long StartTime = System.currentTimeMillis() / 1000;
for (int i = 0; i < loop; ++i) {
loop++;
if (timevalue < ((System.currentTimeMillis() / 1000) - StartTime)) {
loop = 0;
CrossOpb = false;
}
CrossOp.start();
}

I already answered to a similar question. In that case, it was C#, but the concept is the same.
You must not kill threads. Threads must exit on their own will.
Just put a volatile boolean variable somewhere, and set it to true/false, when you want your thread to terminate, then, in the thread, replace the while (true) with a while (myVariable == true/false).
Anyway, you say:
Inside the loop, am going to call 5 procedures ant i thought that if i put each procedure in a thread will make the program making more solutions in a same time than calling normal methods.
Well, that's generally false. If the procedures are data-dependent (each of them depends on the results of the previous one), putting them on threads will change nothing. It might be smarter to put iterations in a pipeline, so that you have 5 threads executing steps of successive iterations. I'm not sure if that's possible for genetic algorithms, and anyway you'll have to handle some special case (e.g. a mutation, that alters the population of partially computed iterations).

How to run a Thread for a specific amount of time:
Here is the basic approach is to keep calculate how long the Thread has run and exit and return the result, which in our case here is details on how long the Thread executed.
NOTE: you must use System.nanoTime() as System.currentTimeMillis() will just return the same thing every time you call it in the method.
I use a Random number to calculate different lifetimes for each of the Callables so that you can see that they don't execute exactly for the time specified but they are very very close, and the variance of the delta is pretty consistent, at least on my machine.
Here a Gist of the code below for easier access.
package com.stackoverflow.Q18818482;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import java.util.Random;
import java.util.concurrent.*;
public class Question18818482
{
public static Random RND;
static
{
RND = new Random();
}
public static void main(final String[] args)
{
try
{
final ExecutorService es = Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors());
final List<Future<String>> results = new ArrayList<>(10);
for (int i = 0; i < 10; i++)
{
results.add(es.submit(new TimeSliceTask(RND.nextInt(10), TimeUnit.SECONDS)));
}
es.shutdown();
while(!results.isEmpty())
{
final Iterator<Future<String>> i = results.iterator();
while (i.hasNext())
{
final Future<String> f = i.next();
if (f.isDone())
{
System.out.println(f.get());
i.remove();
}
}
}
}
catch (InterruptedException e)
{
throw new RuntimeException(e);
}
catch (ExecutionException e)
{
throw new RuntimeException(e);
}
}
public static class TimeSliceTask implements Callable<String>
{
private final long timeToLive;
private final long duration;
public TimeSliceTask(final long timeToLive, final TimeUnit timeUnit)
{
this.timeToLive = System.nanoTime() + timeUnit.toNanos(timeToLive);
this.duration = timeUnit.toMillis(timeToLive);
}
#Override
public String call() throws Exception
{
while( timeToLive <= System.nanoTime() )
{
// simulate work here
Thread.sleep(500);
}
final long end = System.nanoTime();
return String.format("Finished Elapsed Time = %d, scheduled for %d", TimeUnit.NANOSECONDS.toMillis(timeToLive - end), this.duration );
}
}
}
Here is what one runs output looks like
NOTE: All times are in milliseconds
Finished Elapsed Time = 999, scheduled for 1000
Finished Elapsed Time = 2998, scheduled for 3000
Finished Elapsed Time = 5999, scheduled for 6000
Finished Elapsed Time = 1994, scheduled for 2000
Finished Elapsed Time = 8994, scheduled for 9000
Finished Elapsed Time = 6993, scheduled for 7000
Finished Elapsed Time = 6993, scheduled for 7000
Finished Elapsed Time = 5993, scheduled for 6000
Finished Elapsed Time = 5998, scheduled for 6000

After reading the whole last night about threads, i have discovered that the solution for my problem was not that hard.
The idea was to edit the condition of the stopping loop inside the thread so we control it by giving it a specific amount of time to run for it and here is my Example :
class ProcessorCordm extends Thread {
int runningtime;
public ProcessorCordm(int runningtime) {
this.runningtime = runningtime;
}
public void run() {
int loop = 1;
long StartTime = System.currentTimeMillis() / 1000;
for (int i = 0; i < loop; ++i) {
int rdmCross2 = (int) (Math.random() * allPopulation.size()); // Crossover 1st vector
int rdmCross1 = (int) (Math.random() * allPopulation.size());
Vector muted = new Vector();
Vector copy = copi((Vector) allPopulation.get(rdmCross2));
Vector callp = copi((Vector) allPopulation.get(rdmCross1));
muted = crossover(callp, copy);
System.out.println("cross over Between two Randoms ----------->");
affiche_resultat(muted);
addsolution(muted);
loop++;
if (timevalue < ((System.currentTimeMillis() / 1000) - StartTime)) {
loop = 0;
}
}
}
}
So if i want to run my Thread for 10 seconds i only need to :
ProcessorCoG CrossOpg = new ProcessorCoG(10);
And fo my case, I have to call many Threads simultaneously working for a specific TimeValue so i used the ExecutorServiceClass :
ProcessorCoG CrossOpg = new ProcessorCoG(timevalue);//extends Thread class
ProcessorCordm CrossOp = new ProcessorCordm(timevalue);//extends Thread class
ProcessorCordm CrossOp2 = new ProcessorCordm(timevalue);//extends Thread class
MutateGb MutGb = new MutateGb(timevalue);//extends Thread class
MutateRdm MutRdm = new MutateRdm(timevalue);//extends Thread class
MbsRdm MbsR = new MbsRdm(timevalue);//extends Thread class
ExecutorService executor = Executors.newFixedThreadPool(6);
executor.submit(MutGb);
executor.submit(MutRdm);
executor.submit(CrossOp);
executor.submit(CrossOp2);
executor.submit(CrossOpg);
executor.submit(MbsR);