View the program in our Progressive Web App
Program for stream Global Optimization
Sunday
Monday
Monday, 8:30-10:00
MA-24: Recent Results in Global Optimization 1
Stream: Global Optimization
Room: Virtual Room 24
Chair(s):
Mario Alberto Mendoza Villalba
-
Duality for nonconvex optimization problems with abstract convex functions
Monika Syga, Ewa Bednarczuk -
LIPSCHITZ GLOBAL OPTIMIZATION
Yaroslav Sergeyev, Dmitri Kvasov, Marat Mukhametzhanov, Maria Chiara Nasso -
Escape Strategies Algorithm (ESSA), a new meta heuristic algorithm for global optimization problems, inspired in pre-predator interaction
Mario Alberto Mendoza Villalba, Jesus David Galarcio Noguera, Jorge Mario López Pereira
Monday, 10:30-12:00
MB-24: Consensus-Based Global Optimization
Stream: Global Optimization
Room: Virtual Room 24
Chair(s):
Claudia Totzeck
-
From particle swarm optimization to consensus based optimization: stochastic modeling and mean-field limit
Sara Grassi -
Derivative-free Bayesian inversion using multiscale dynamics
Urbain Vaes -
Recent advances in consensus-based global optimization
Claudia Totzeck -
Consensus-based optimization methods converge globally in mean-field law
Massimo Fornasier
Monday, 12:30-14:00
MC-24: Recent Results in Global Optimization 2
Stream: Global Optimization
Room: Virtual Room 24
Chair(s):
Syuuji Yamada
-
Dual Cutting Plane Method for Nonconvex Optimization
Jaehwan Jeong, Chanaka Edirisinghe -
An Exact Solution Method for Concave Minimization Problems
Arka Das, Ankur Sinha, Guneshwar Anand, Sachin Jayaswal -
A global optimization algorithm incorporating a procedure of listing KKT points for a quadratic fractional programming problem
Syuuji Yamada
Monday, 14:30-16:00
MD-24: Optimization with machine learning surrogate models
Stream: Global Optimization
Room: Virtual Room 24
Chair(s):
Alexander Mitsos, Chryssa Kappatou
-
Expensive black-box optimization in process systems engineering
Antonio del Rio Chanona, Damien van de Berg, Thomas Savage, Panagiotis Petsagkourakis, Dongda Zhang, Nilay Shah -
Uncertainty measures and hierarchical acquisition functions for tree-based black-box optimization
Alexander Thebelt, Robert M. Lee, Nathan Sudermann-Merx, David Walz, Ruth Misener -
A data-driven inverse optimization approach to learning surrogate optimizers
Rishabh Gupta, Qi Zhang -
Deterministic global optimization with surrogate models
Chryssa Kappatou, Dominik Bongartz, Jaromil Najman, Susanne Sass, Artur M. Schweidtmann, Alexander Mitsos