Process / pipelineSimulation / optimization
确定性粒子群优化 — 无随机噪声的收敛保证的群体搜索
确定性粒子群优化 (DPSO) 从经典 PSO 中移除了随机系数，用固定的认知和社会加速度参数取而代之。粒子沿着完全可预测的轨迹在搜索空间中移动，从而能够进行可复现的收敛性分析，并保证在连续和组合优化问题中具有终止行为。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Kennedy, J., Eberhart, R. (1995). Particle swarm optimization. Proceedings of ICNN'95 — International Conference on Neural Networks, vol. 4, pp. 1942–1948. IEEE. DOI: 10.1109/ICNN.1995.488968 ↗
- Clerc, M., Kennedy, J. (2002). The particle swarm — explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation, 6(1), 58–73. DOI: 10.1109/4235.985692 ↗
如何引用本页
ScholarGate. (2026, June 3). Deterministic Particle Swarm Optimization (DPSO). ScholarGate. https://scholargate.app/zh/simulation/deterministic-particle-swarm-optimization
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 蚁群优化优化↔ compare
- 遗传算法优化↔ compare
- 多目标粒子群优化 (MOPSO)仿真↔ compare
- 粒子群优化 (PSO)优化↔ compare
- 模拟退火优化↔ compare
- 随机粒子群优化仿真↔ compare