Consensus based optimization

Consensus based optimization (CBO) ^[1] is a method to obtain solutions for global optimization problems of the form $\min _{x\in {\cal {X}}}f(x),$ where $f:{\mathcal {X}}\to \mathbb {R}$ denotes the objective function acting on the state space ${\cal {X}}$ . The algorithm is based on particles exploring the state space, while communicating with each other to update their positions. In this sense, CBO is comparable to wind driven optimization^[2], particle swarm optimization or Simulated annealing. However, compared to other heuristics, CBO was designed to have a well-posed mean-field limit

Convergence

Variants

Polarization

References

^ Pinnau, René; Totzeck, Claudia; Tse, Oliver; Martin, Stephan (January 2017). "A consensus-based model for global optimization and its mean-field limit". Mathematical Models and Methods in Applied Sciences. 27 (1): 183–204. arXiv:1604.05648. doi:10.1142/S0218202517400061. ISSN 0218-2025. S2CID 119296432.
^ "The Wind Driven Optimization Technique and its Application in Electromagnetics | IEEE Journals & Magazine | IEEE Xplore". ieeexplore.ieee.org. Retrieved 2024-02-03.

[1] Pinnau, René; Totzeck, Claudia; Tse, Oliver; Martin, Stephan (January 2017). "A consensus-based model for global optimization and its mean-field limit". Mathematical Models and Methods in Applied Sciences. 27 (1): 183–204. arXiv:1604.05648. doi:10.1142/S0218202517400061. ISSN 0218-2025. S2CID 119296432.

[2] "The Wind Driven Optimization Technique and its Application in Electromagnetics | IEEE Journals & Magazine | IEEE Xplore". ieeexplore.ieee.org. Retrieved 2024-02-03.

[1]

[2]

Convergence

Variants

Polarization

See also

References