Abstract
This paper introduces a novel stochastic and population-based binary optimization method inspired by social psychology. It is called Social Impact Theory based Optimization (SITO). The method has been developed with the use of some simple modifications of simulations of Latané's Dynamic Social Impact Theory. The usability of the algorithm is demonstrated via experimental testing on some test problems. The results showed that the initial version of SITO performs comparably to the simple Genetic Algorithm (GA) and the binary Particle Swarm Optimization (bPSO). © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Macaš, M., & Lhotská, L. (2007). Social impact theory based optimizer. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4648 LNAI, pp. 635–644). Springer Verlag. https://doi.org/10.1007/978-3-540-74913-4_64
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
