As my question states, the problem I am having is finding a sensible way to search a large space. Any help or insight that could be provided would be hugely appreciated.
Currently I am trying to search through a space of possible investment strategies. This space has been restricted to 3 possible assets (Equity, Cash and Bonds) across 100 years where strategies are constant for 10 years at a time. I have also constrained the area by only allowing 100% investment in one asset or a 50/50 split between two. All of the fund must be invested at each time. This means that there are 10 times to choose between 6 possible combinations of investments. I have already preformed a basic search of the space using a labour intensive method of Genetic Algorithms which requires me to choose suitably optimal strategies across larger times, working my way down to decades starting at 50 year blocks. However I believe that there would be a better solution but my lack of knowledge in optimization is hindering me here. A strategy is ran through a programme to provide quantiles of a fund life which are then matched to given criteria.This is what indicates the suitability of a strategy.
I have been looking into using Bellman's equation but since it requires markovian assumptions I don't know if I can apply this. If anyone has any ideas that could be applied it would be a great help.
If anything I've said requires clarification or if I have been a bit vague on some information please let me know.
Thanks in advance.