Abstract
Previously, a variation of Asynchronous Population Based Hill Climbing was applied to a discrete optimisation task from the field of electronic circuit design with a challenging 9 dimensional search space. The algorithm exhibited a certain behaviour, which is analysed in this new research. A problem was the asynchronous nature of the search algorithm, which did not allow the search threads to save the internal state data into log files. Instead, a novel monitoring strategy had to be developed, which accesses this internal data via shared memory in specified times intervals. It was possible to show that the algorithm under investigation is capable of switching between exploration and exploitation of the search space during the search. This prevents the algorithm from being stuck in a local optimum.