Pyramid search: finding solutions for deceptive problems quickly in genetic programming
Victor B. Ciesielski, Xiang Li · 2004
In deceptive problems many runs lead to suboptimal solutions and it can be difficult to escape from these local optima and find the global best solution. We propose a pyramid search strategy for these kinds of problems. In the pyramid strategy a number of populations are initialised and independently evolved for a number of generations at which point the worst performing populations are discarded. This evolve/discard process is continued until the problem is solved or one population remains. We show that for a number of deceptive problems the pyramid strategy results in a higher probability of success with fewer evaluations and a lower standard deviation of the number evaluations to success than the conventional approach of running to a maximum number of generations and then restarting.