How to implement an asynchronous parallel genetic algorithm using the MATLAB Parallel Computing Toolbox?

Question

I am struggling to find a way to implement an asynchronous evolutionary process in MATLAB.

I've already implemented a "standard" GA that evaluates the fitness of individuals in parallel using MATLAB's parfor routine. However, this also means that the different workers in my parallel pool have to wait for the last worker to finish his assesment before I can create a new generation and continue with my parallel fitness evaluation. But when the fitness assessment time is very heterogeneous, such an approach can involve significant idle times.

The suggested solution in the literature is what is sometimes called asynchronous evolution. It means that there are no generations anymore, instead every time a worker becomes idle we immediately let him breed a new individual and evalute its fitness. As such there is hardly any idle time as no worker has to wait for others to complete their fitness assessment. The only problem is that those parallel threads/workers need to work on the same population, i.e. they need to communicate to each other whenever they want to breed a new individual (because they need to select parents out of a population that is constantly altered by the workers).

Now ideally you would control each worker separately, letting him access the joint population to select parents, evaluate the offspring's fitness and then replace a parent in the joint population. That involves an ongoing iterative process where parallel workers need to exchange and alter joint information and doing independent fitness evaluation.

My big question is: How can this be achieved in MATLAB?

Things I've already tried:

• MATLAB's 'spmd'-functionality using the labSend and labReceive functions but this also seems to involve waiting for other workers.

• creating jobs and assigning them tasks. Does not seem to work as multiple jobs are processed sequentially on the cluster. Only tasks within a job use multiple workers but that fails since you can't assign tasks dynamically (you always have to submit the whole job anew to the queue.

• parfeval in a recursive while statement. I do not see how this would reduce waiting time.

So does anyone know a way how to implement something like this in MATLAB?