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Taguchi-Particle Swarm Optimization for Numerical Optimization
International Journal of Swarm Intelligence Research, 2010In this work, a hybrid Taguchi-Particle Swarm Optimization (TPSO) is proposed to solve global numerical optimization problems with continuous and discrete variables. This hybrid algorithm combines the well-known Particle Swarm Optimization Algorithm with the established Taguchi method, which has been an important tool for robust design.
T. O. Ting, H. C. Ting, T. S. Lee
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A Hybrid Particle Swarm Optimization for Numerical Optimization
2009 International Conference on Business Intelligence and Financial Engineering, 2009Particle Swarm Optimization (PSO) has shown its good performance on numerical function problems. However, on some multimodal functions the PSO easily suffers from premature convergence because of the rapid decline in velocity. This paper presents a hybrid PSO for numerical optimization, namely HPSO, which employs opposition-based learning (OBL) and a ...
Zhengang Ning +3 more
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PSO-sono: A novel PSO variant for single-objective numerical optimization
Information Sciences, 2022Zhenyu Meng, Guojun Mao
exaly
Numerical Methods for Unconstrained Optimization
2017Unconstrained optimization is the search for the maximum or minimum of a function with no restriction on the values of the variables. At the same time, it forms the basis for methods of constrained optimization in the next chapter. Zero-order methods use only function values, progress made in the previous step pointing the way to the next step.
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An optimization numerical spiking neural P system for solving constrained optimization problems
Information Sciences, 2023Gexiang Zhang, Haina Rong
exaly