Global optimization by Darwin and Boltzmann mixed strategy

This paper presents a Darwin and Boltzmann mixed strategy to solve the global optimization problems. The algorithm is based on the integration of the Darwin strategy and the Boltzmann annealing strategy, it is a hybrid of the Stochastic Evolution (SE) and the Simulated Annealing (SA). The proposed algorithm is proved to converge asymptotically to the global optimal solutions and its approximation implementation has shown to be polynomial in complexity. Experimental results show that the proposed algorithm is more efficient than the SA algorithm and is comparable to other methods on six well-known test problems.