5 papers
Exploiting Structure with Anisotropic Consensus-Based Optimization
Sabrina Bonandin, Konstantin Riedl, Sara Veneruso
Anisotropic consensus-based optimization (CBO), a multi-agent metaheuristic derivative-free optimization method, which reliably finds global minima of nonsmooth and nonconvex objec…
Strong Global Convergence of the Consensus-Based Optimization Algorithm
Sabrina Bonandin, Konstantin Riedl, Sara Veneruso
Consensus-based optimization (CBO) is a multi-agent metaheuristic derivative-free optimization algorithm that has proven to be capable of globally minimizing nonconvex nonsmooth fu…
Consensus-based algorithms for stochastic optimization problems
Sabrina Bonandin, Michael Herty
We address an optimization problem where the cost function is the expectation of a random mapping. To tackle the problem two approaches based on the approximation of the objective…
Kinetic variable-sample methods for stochastic optimization problems
Sabrina Bonandin, Michael Herty
We discuss kinetic-based particle optimization methods and variable-sample strategies for problems where the cost function represents the expected value of a random mapping. Kineti…
Effects of heterogeneous opinion interactions in many-agent systems for epidemic dynamics
Sabrina Bonandin, Mattia Zanella
In this work we define a kinetic model for understanding the impact of heterogeneous opinion formation dynamics on epidemics. The considered many-agent system is characterized by n…