Abstract
The paper presents FMOPSO a multiobjective optimization method that uses a Particle Swarm Optimization algorithm enhanced with a Fuzzy Logic-based controller. Our implementation makes use of a number of fuzzy rules as well as dynamic membership functions to evaluate search spaces at each iteration. The method works based on Pareto dominance and was tested using standard benchmark data sets. Our results show that the proposed method is competitive with other approaches reported in the literature.
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Yazdani, H., Kwasnicka, H., Ortiz-Arroyo, D. (2011). Multiobjective Particle Swarm Optimization Using Fuzzy Logic. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_22
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DOI: https://doi.org/10.1007/978-3-642-23935-9_22
Publisher Name: Springer, Berlin, Heidelberg
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