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Sökning: WFRF:(Morales Castañeda Bernardo)

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1.
  • Morales-Castañeda, Bernardo, et al. (författare)
  • A Novel Diversity-Aware Inertia Weight and Velocity Control for Particle Swarm Optimization
  • 2023
  • Ingår i: 2023 IEEE Congress on Evolutionary Computation (CEC). - : IEEE Press. - 9798350314588 - 9798350314588
  • Konferensbidrag (refereegranskat)abstract
    • Particle Swarm Optimization (PSO) has efficiently solved several real-world applications and optimization problems. However, it has shortcomings, such as premature convergence and stagnation at local minima. Inertia weight is a parameter of this algorithm that controls the global and local exploration and exploitation capability by determining the influence of the previous velocity on its current motion. Therefore, this article proposes a PSO with a Diversity-aware Inertia and Velocity Control (PSOIVC) algorithm to improve the PSO performance. The PSOIVC employs a novel diversity-aware inertia weight and velocity control approach to tune the parameters to produce a trade-off between exploration and exploitation of the algorithm using the dimension-wise diversity. The PSOIVC algorithm is compared with eight algorithms, including variants of the PSO, on a set of 30 benchmark functions for a single objective real parameter in 30 and 50 dimensions. Based on the results, the proposal presents significant outcomes according to the average values obtained for both comparisons; because it performed similarly or better than the other algorithms in 23/30 and 16/30 for 30 and 50 dimensions, respectively.
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2.
  • Morales-Castañeda, Bernardo, et al. (författare)
  • Improving the Convergence of the PSO Algorithm with a Stagnation Variable and Fuzzy Logic
  • 2023
  • Ingår i: 2023 IEEE Congress on Evolutionary Computation (CEC). - : IEEE Press. - 9798350314588 - 9798350314588
  • Konferensbidrag (refereegranskat)abstract
    • Particle swarm optimization (PSO) is essential to evolutionary computation algorithms (ECA). The PSO has some drawbacks as premature convergence and stagnation at local minima. Inertia weight is a parameter that controls the global and local exploration and exploitation capability in the PSO by determining the influence of the previous velocity on its current motion. This article proposes using a stagnation counter that verifies the times the PSO is stuck in the same fitness value. In the proposed fuzzy controlled PSO with stagnation coefficient (FCPSO), a fuzzy controller is designed to tune the inertia weight based on the population's diversity and the search's stagnation. This modification allows the PSO to escape from suboptimal values enhancing its search capabilities. The FCPSO is tested over 28 benchmark functions in 50 dimensions. Besides, it has been compared with nine optimization algorithms from the state-of-the-art. The experiments and comparisons suggest that the FCPSO is an interesting tool for solving complex optimization problems.
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  • Resultat 1-2 av 2

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