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This paper studies the efficiency and robustness of some recent and well known population set based direct search global optimization methods such as Controlled Random Search, Differential Evolution, and the Genetic Algorithm. Some modifications are made to Differential Evolution and to the Genetic Algorithm to improve their efficiency and robustness. All(More)
In this paper we propose a new version of the Controlled Random Search (CRS) algorithm of Price 13, 14, 15]. The new algorithm has been tested on thirteen global optimization test problems. Numerical experiments indicate that the resulting algorithm performs considerably better than the earlier versions of the CRS algorithms. The algorithm, therefore, could(More)
A memory-based simulated annealing algorithm is proposed which fundamentally diiers from the previously developed simulated annealing algorithms for continuous variables by the fact that a set of points rather than a single working point is used. The implementation of the new method does not need any properties of the function being optimized. The method is(More)
In this paper, a real-coded genetic algorithm (RCGA) which incorporates an exploratory search mechanism based on vector projection termed projection-based RCGA (PRCGA) is benchmarked on the noisefree BBOB 2013 testbed. It is an enhanced version of RCGA-P in [22, 23]. The projection operator incorporated in PRCGA shows promising exploratory search capability(More)