Manuel Berkemeier

M.Sc. in Applied Mathematics, 2019; currently PhD student in the Data Science and Engineering group at Paderborn University, Germany.

Talks:

14:30 UTC

Surrogate-Assisted Multi-Objective Optimization with Constraints

07/28/2023, 2:30 PM — 2:40 PM UTC
32-D463 (Star)

We present the key ideas for finding first-order critical points of multi-objective optimization problems with nonlinear objectives and constraints. A gradient-based trust-region algorithm is modified to employ local, derivative-free surrogate models instead, and a so-called Filter ensures convergence towards feasibility. We show results of a prototype implementation in Julia, relying heavily on JuMP and suitable LP or QP solvers, that confirm the use of surrogates to reduce function calls.

Platinum sponsors

JuliaHub

Gold sponsors

ASML

Silver sponsors

Pumas AIQuEra Computing Inc.Relational AIJeffrey Sarnoff

Bronze sponsors

Jolin.ioBeacon BiosignalsMIT CSAILBoeing

Academic partners

NAWA

Local partners

Postmates

Fiscal Sponsor

NumFOCUS