الگوریتم بهینه سازی تصمیم جمعی: یک روش بهینه سازی اکتشافی جدید

Recently, inspired by nature, diversiform successful and effective optimization methods have been proposed for solving many complex and challenging applications in different domains. This paper proposes a new meta-heuristic technique, collective decision optimization algorithm (CDOA), for training artificial neural networks. It simulates the social behavior of human based on their decision-making characteristics including experience-based phase, others'-based phase, group thinking-based phase, leader-based phase and innovation-based phase. Different corresponding operators are designed in the methodology. Experimental results carried out on a comprehensive set of benchmark functions and two nonlinear function approximation examples demonstrate that CDOA is competitive with respect to other state-of-art optimization algorithms.