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arXiv · 2205.04880

Consensus based optimization via jump-diffusion stochastic differential equations

D. Kalise·A. Sharma·M. V. Tretyakov
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Abstract

We introduce a new consensus based optimization (CBO) method where interacting particle system is driven by jump-diffusion stochastic differential equations. We study well-posedness of the particle system as well as of its mean-field limit. The major contributions of this paper are proofs of convergence of the interacting particle system towards the mean-field limit and convergence of a discretized particle system towards the continuous-time dynamics in the mean-square sense. We also prove convergence of the mean-field jump-diffusion SDEs towards global minimizer for a large class of objective functions. We demonstrate improved performance of the proposed CBO method over earlier CBO methods in numerical simulations on benchmark objective functions.

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BibTeXRIS

D. Kalise, A. Sharma, M. V. Tretyakov. 2022-05-10. Consensus based optimization via jump-diffusion stochastic differential equations. https://doi.org/10.1142/s0218202523500082

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