Social cognitive optimization
Social Cognitive Optimization (SCO) is a population-based metaheuristic optimization algorithm which was developed in 2002 [1] [2] . This algorithm is based on the social cognitive theory, and the key point of the ergodicity is the process of individual learning of a set of agents with their own memory and their social learning of the knowledge points in the social sharing library.
References
- ^ Xie, Xiao-Feng; Zhang, Wen-Jun; Yang, Zhi-Lian (2002). Social cognitive optimization for nonlinear programming problems. International Conference on Machine Learning and Cybernetics (ICMLC), Beijing, China: 779-783.
- ^ Xie, Xiao-Feng; Zhang, Wen-Jun (2004). Solving engineering design problems by social cognitive optimization. Genetic and Evolutionary Computation Conference (GECCO), Seattle, WA, USA: 261-262.