Program for stream Global Optimization

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

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

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

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