Jump to content

Social cognitive optimization

Edit links
From Wikipedia, the free encyclopedia
This is an old revision of this page, as edited by Xfxie (talk | contribs) at 00:37, 6 January 2015. The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Social Cognitive Optimization (SCO) is a population-based metaheuristic optimization algorithm which was developed in 2002 [1] . 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. It has been used for solving continuous optimization [2][3], integer programming [4], and combinatorial optimization problems. It has been incorporated into the NLPSolver extension of Calc in Apache OpenOffice.

References

  1. ^ 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.
  2. ^ 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.
  3. ^ Xu, Gang-Gang; Han, Luo-Cheng; Yu, Ming-Long; Zhang, Ai-Lan (2011). Reactive power optimization based on improved social cognitive optimization algorithm. International Conference on Mechatronic Science, Electric Engineering and Computer (MEC), Jilin, China: 97-100.
  4. ^ Fan, Caixia (2010). Solving Integer Programming Based on Maximum Entropy Social Cognitive Optimization Algorithm. International Conference on Information Technology and Scientific Management (ICITSM), Tianjing, China: 795-798.
Retrieved from "https://en.wikipedia.org/w/index.php?title=Social_cognitive_optimization&oldid=641164830"