Globally Managed Parallel Optimization¶
Introduction¶
GloMPO (Globally Managed Parallel Optimization) is an optimisation framework which supervises and controls traditional optimization routines in real-time using customisable heuristics. By monitoring the performance of each of these optimizers in real time, the GloMPO manager is able to make decisions to terminate and start new optimizers in better locations.
GloMPO is designed to be used on high-dimensional, expensive, multimodal, black-box optimization problems but simpler problems are not precluded.
The three main advantages to optimization in this way:
Optimizers are pushed out of local minima, thus more and better solutions are more likely to be found;
Through terminations of optimizers stuck in local minima, function evaluations can be used more efficiently;
The use of multiple optimizers allows multiple competitive/equivalent solutions to be found.
The user is advised to first work through the introduction and then the examples which give a good introduction to the GloMPO package and its components before diving deeper into the rest of the documentation.