We propose a heterogeneous island model where each of the islands can run a different optimization algorithm. The distributed computation is managed by a central planner, that re-plans the methods during the run of the algorithm -- less successful methods are removed while new instances of more successful methods are added.
We show that this re-planning improves the performance of the optimization algorithm.