In this work we are interested in stochastic particle methods for multi-objective optimization.
The problem is formulated via scalarization using parametrized, single-objective sub …

Motivated by numerical challenges in first-order mean field games (MFGs) and the weak
noise theory for the Kardar-Parisi-Zhang equation, we consider the problem of vanishing …

Scalarization allows to solve a multi‐objective optimization problem by solving many single‐
objective sub‐problems, uniquely determined by some parameters. In this work, several …

We investigate the effect of linear diffusion and interactions with the domain boundary on
swarm equilibria by analyzing critical points of the associated energy functional. Through …

We investigate a general class of models for swarming/self-collective behaviour in domains
with boundaries. The model is expressed as a stochastic system of interacting particles …

Stochastic particle methods in optimization constitute a popular class of heuristic techniques
where a set of possible solutions is iteratively updated according to deterministic and …

We establish the zero-diffusion limit for both continuous and discrete aggregation models
over convex and bounded domains. Compared with a similar zero-diffusion limit derived in …

We investigate the zero-diffusion limit for both continuous and discrete aggregation-diffusion
models over convex and bounded domains. Our approach relies on a coupling method …

This thesis involves the study of a well-known swarming model with interaction and external
potentials in one and two dimensions. We refer to this model as the plain aggregation model …