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초록
In this paper, we provide an analytical framework for investigating the efficiency of a consensus-based model for tackling global optimization problems. This work justifies the optimization algorithm in the mean-field sense showing the convergence to the global minimizer for a large class of functions. Theoretical results on consensus estimates are then illustrated by numerical simulations where variants of the method including nonlinear diffusion are introduced.
키워드
Global optimization; opinion dynamics; consensus formation; agent-based models; stochastic dynamics; mean-field limit; FLOCK SOLUTIONS; PARTICLE; METAHEURISTICS; DYNAMICS; MODELS
- 제목
- An analytical framework for consensus-based global optimization method
- 저자
- Carrillo, Jose A.; Choi, Young-Pil; Totzeck, Claudia; Tse, Oliver
- 발행일
- 2018-06-15
- 유형
- Article
- 권
- 28
- 호
- 6
- 페이지
- 1037 ~ 1066