A novel swarm optimization algorithm based on Social Force model for multimodal functions

Social Force model is a dynamic model used to the simulation of crowd behaviors. The Social Force model explains the formation of self-organization from the dynamic. In this paper, a new Swarm Optimization algorithm based on Social Force model (SFSO) is proposed. The SFSO algorithm is a population based optimization technique which is inspired from the behaviors of pedestrian. In SFSO algorithm, the searching characteristics of the pedestrians, such as target selecting, information exchange, overtaking search and scene understanding, are the special abstraction to the pedestrians´ movement and psychology. The results on benchmark problems indicated that SFSO is a promising optimization method and an effective approach to solve multimodal numerical optimization problems.