Formulation and parameter selection of multi-objective deterministic particle swarm for simulation-based optimization

@article{Pellegrini2017FormulationAP,
  title={Formulation and parameter selection of multi-objective deterministic particle swarm for simulation-based optimization},
  author={Riccardo Pellegrini and Andrea Serani and Cecilia Leotardi and Umberto Iemma and Emilio Fortunato Campana and Matteo Diez},
  journal={Appl. Soft Comput.},
  year={2017},
  volume={58},
  pages={714-731}
}
Global derivative-free deterministic algorithms are particularly suitable for simulation-based optimization, where often the existence of multiple local optima cannot be excluded a priori, the derivatives of the objective functions are not available, and the evaluation of the objectives is computationally expensive, thus a statistical analysis of the optimization outcomes is not practicable. Among these algorithms, particle swarm optimization (PSO) is advantageous for the ease of implementation… CONTINUE READING

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