CODMA: A Novel Global Optimization Algorithm based on Open Source Development Model Algorithm with Chaotic Exploration

The open source Development Model Algorithm (ODMA) that was recently introduced has shown its good performance in optimization problems. In this algorithm each point in solution space of the given function has considered as open source software. The considered software (point in the solution space) evolves over time by open source development mechanism. In this paper we present a modified ODMA combine with chaos theory (CODMA). Chaos as a kind of dynamic behavior of nonlinear systems has raised enormous interest in different fields of sciences such as chaos control, pattern recognition, optimization theory and so on. Optimization algorithms based on the chaos theory are stochastic search methodologies that differ from any of the existing evolutionary computation and swarm intelligence methods. General ODMA as like as many evolutionary algorithm may fall into local minimum trap, during the search process, to mitigate this problem we increased the exploration ability of the ODMA, using chaotic behaviour in the Moving toward leading softwares operation. This algorithm is tested by 4 benchmark functions and the results show that the algorithm approach to the global minimum of these functions successfully, also the algorithm is compared with ODMA, GA and PSO and as we shown CODMA have better accuracy and convergence for finding global minima.