A Random Search Approach to Finding the Global Minimum
Tunçhan Cura · 2010
In this study, a new random search algorithm is proposed for finding the global minimum. It is tested on 21 benchmark minimization problems, and its solutions are compared to those of several previously proposed techniques: an adaptive random search, a heuristic random search, the ant colony approach, the discrete filled function algorithm, and the dynamic random search technique. The results of these numerical experiments show that the proposed algorithm is efficient and reliable.