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particle swarm features improvement #647

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@damarro3 damarro3 commented Nov 11, 2025

Extend canonical PSO with adaptive and diversity-preserving mechanisms:

  • Add time-varying acceleration coefficients (TVAC) for dynamic exploration/exploitation balance
  • Add chaotic inertia weight using logistic map for escaping local optima
  • Add velocity mutation threshold to prevent particle stagnation (HPSO)
  • Add velocity clamping to prevent explosive divergence
  • Add multiple initialization strategies: Latin Hypercube Sampling and Opposition-Based Learning
  • Add mutation operators: Gaussian and Cauchy with configurable application strategies (GlobalBestOnly, AllParticles, BelowAverage)
  • Implement iteration tracking via argmin State trait for time-varying strategies

All enhancements maintain backward compatibility with canonical PSO defaults.
@damarro3
feat(particleswarm): add advanced PSO strategies and enhancements
bd77cf2 
Extend canonical PSO with adaptive and diversity-preserving mechanisms: - Add time-varying acceleration coefficients (TVAC) for dynamic exploration/exploitation balance - Add chaotic inertia weight using logistic map for escaping local optima - Add velocity mutation threshold to prevent particle stagnation (HPSO) - Add velocity clamping to prevent explosive divergence - Add multiple initialization strategies: Latin Hypercube Sampling and Opposition-Based Learning - Add mutation operators: Gaussian and Cauchy with configurable application strategies (GlobalBestOnly, AllParticles, BelowAverage) - Implement iteration tracking via argmin State trait for time-varying strategies All enhancements maintain backward compatibility with canonical PSO defaults.
@damarro3
efactor(particleswarm): derive Default for enum types
cc36120 
Replace manual Default implementations with derived implementations using #[derive(Default)] and #[default] attributes for InitializationStrategy, MutationStrategy, and MutationApplication.
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