Improved performance of PSO with self-adaptive parameters for computing the optimal design of Water Supply Systems

@article{Montalvo2010ImprovedPO,
  title={Improved performance of PSO with self-adaptive parameters for computing the optimal design of Water Supply Systems},
  author={Idel Montalvo and Joaqu{\'i}n Izquierdo and Rafael P{\'e}rez-Garc{\'i}a and Manuel Herrera},
  journal={Eng. Appl. of AI},
  year={2010},
  volume={23},
  pages={727-735}
}
This paper deals with a new variant of Particle Swarm Optimization (PSO) in which no a priori parameter tuning is necessary. PSO, as an efficient and powerful problem-solving technique, has been widely used, but, as in other Evolutionary Algorithms (EA), appropriate adjustment of its parameters is cumbersome and usually requires a lot of time, effort and luck. Thus, a self-adaptive framework is proposed to improve the robustness of the PSO. In this paper, within a framework that also includes… CONTINUE READING
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