Adaptive Heuristic Applied to Large Constraint Optimisation Problem

The article presents experimental results achieved by Free Search on optimization of 100 dimensional version of so called bump test problem. Free Search is adaptive heuristic algorithm. It operates on a set of solutions called population and it can be classified as population-based method. It gradually modifies a set of solutions according to the prior defined objective function. The aim of the study is to identify how Free Search can diverge from one starting location in the middle of the search space in comparison to start from random locations in the middle of the search space and start from stochastic locations uniformly generated within the whole search space. The results achieved from the experiments with above initialization strategies are presented. A discussion focuses on the ability of Free Search to diverge from one location if the process stagnates in local trap during the search. The article presents, also, the values of the variables for the best achieved results, which could be used for comparison to other methods and further investigation.