569 RWTH Publication No: 844169        2022       
TITLE A consensus-based algorithm for multi-objective optimization and its mean-field description
AUTHORS Giacomo Borghi, Michael Herty, Lorenzo Pareschi
ABSTRACT We present a multi-agent algorithm for multi-objective optimization problems, which extends the class of consensus-based optimization methods and relies on a scalarization strategy. The optimization is achieved by a set of interacting agents exploring the search space and attempting to solve all scalar sub-problems simultaneously. We show that those dynamics are described by a mean-field model, which is suitable for a theoretical analysis of the algorithm convergence. Numerical results show the validity of the proposed method.
KEYWORDS
DOI 10.1109/CDC51059.2022.9993095
PUBLICATION CDC 22 : Conference on Decision and Control
Dec. 6-9, 2022, Cancún, Mexico
IEEE, pp. 4131-4136