In standard particle swarm optimization (PSO), the best particle in each neighborhood exerts its influence over other particles in the neighborhood. In this paper, we propose fuzzy PSO, a generalization which differs from standard PSO in the following respect: charisma is defined to be a fuzzy variable, and more than one particle in each neighborhood can have a non-zero degree of charisma, and, consequently, is allowed to influence others to a degree that depends on its charisma. We evaluate our model on the weighted maximum satisfiability (maxsat) problem, comparing performance to standard PSO and to Walk-Sat.

Meeting Name

IEEE International Joint Conference on Neural Networks, 2005


Electrical and Computer Engineering

Keywords and Phrases

Charisma; Computability; Fuzzy Set Theory; Fuzzy Variable; Particle Swarm Optimisation; Particle Swarm Optimization; Weighted Maximum Satisfiability Problem

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





© 2005 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

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