Imperial College London
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Dr Dante Kalise

Faculty of Natural Sciences, Department of Mathematics

Reader in Computational Optimisation and Control
 
 
 
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Contact

 

d.kalise-balza Website CV

 
 
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Location

 

742Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Kalise:2023:10.1142/S0218202523500082,
author = {Kalise, D and Sharma, A and Tretyakov, M},
doi = {10.1142/S0218202523500082},
journal = {Mathematical Models and Methods in Applied Sciences (M3AS)},
pages = {289--339},
title = {Consensus based optimization via jump-diffusion stochastic differential equations},
url = {http://dx.doi.org/10.1142/S0218202523500082},
volume = {33},
year = {2023}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - We introduce a new consensus-based optimization (CBO) method where an interacting particle system is driven by jump-diffusion stochastic differential equations (SDEs). 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.
AU  - Kalise,D
AU  - Sharma,A
AU  - Tretyakov,M
DO  - 10.1142/S0218202523500082
EP  - 339
PY  - 2023///
SN  - 0218-2025
SP  - 289
TI  - Consensus based optimization via jump-diffusion stochastic differential equations
T2  - Mathematical Models and Methods in Applied Sciences (M3AS)
UR  - http://dx.doi.org/10.1142/S0218202523500082
UR  - http://hdl.handle.net/10044/1/102694
VL  - 33
ER  -
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