On the mean-field limit for the consensus-based optimization

Abstract

This paper is concerned with the large particle limit for the consensus-based optimization (CBO), which was postulated in the pioneering works [6,28]. In order to solve this open problem, we adapt a compactness argument by first proving the tightness of the empirical measures $\{{\mu }^N{\}}_{N\ge 2}$ associated to the particle system and then verifying that the limit measure $\mu$ is the unique weak solution to the mean-field CBO equation. Such results are extended to the model of particle swarm optimization (PSO).

References in corpus (1)

• Binary interaction methods for high dimensional global optimization and machine learning

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