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Robust Particle Swarm Optimization — Metaheuristik berasaskan kawanan yang peka terhadap ketidakpastian

Robust Particle Swarm Optimization (Robust PSO) melanjutkan metaheuristik PSO klasik untuk mengambil kira ketidakpastian secara eksplisit dalam fungsi objektif, kekangan, atau pembolehubah keputusan. Berbanding mengoptimumkan satu objektif nominal tunggal, setiap penyelesaian calon dinilai merentasi satu set senario ketidakpastian, dan kecergasan dinilai berdasarkan kriteria ketahanan seperti prestasi kes terburuk atau nilai jangkaan, menghasilkan penyelesaian yang kekal hampir optimum walaupun apabila keadaan menyimpang daripada andaian nominal.

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Sumber

  1. Kennedy, J., Eberhart, R. C., & Shi, Y. (2001). Swarm Intelligence. Morgan Kaufmann Publishers. ISBN: 9781558605954
  2. Dellino, G., Kleijnen, J. P. C., & Meloni, C. (2010). Robust optimization in simulation: Taguchi and Response Surface Methodology. International Journal of Production Economics, 125(1), 52–59. DOI: 10.1016/j.ijpe.2009.12.003

Cara memetik halaman ini

ScholarGate. (2026, June 3). Robust Particle Swarm Optimization — Uncertainty-aware swarm-based metaheuristic. ScholarGate. https://scholargate.app/ms/simulation/robust-particle-swarm-optimization

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ScholarGateRobust Particle Swarm Optimization (Robust Particle Swarm Optimization — Uncertainty-aware swarm-based metaheuristic). Dicapai 2026-06-15 daripada https://scholargate.app/ms/simulation/robust-particle-swarm-optimization · Set data: https://doi.org/10.5281/zenodo.20539026