方法证据记录
Robust Particle Swarm Optimization
Robust Particle Swarm Optimization (Robust PSO) extends the classical PSO metaheuristic to explicitly account for uncertainty in the objective function, constraints, or decision variables. Rather than optimizing a single nominal objective, each candidate solution is evaluated over a set of uncertainty scenarios, and fitness is judged by a robustness criterion such as worst-case performance or expected value, yielding solutions that remain near-optimal even when conditions deviate from nominal assumptions.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Robust Particle Swarm Optimization — Uncertainty-aware swarm-based metaheuristic
分类方法记录 · process-pipeline / simulation
- Kennedy, J., Eberhart, R. C., & Shi, Y. (2001). Swarm Intelligence. Morgan Kaufmann Publishers. · ISBN 9781558605954
- 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
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