In the last decades, the increase in computational power led to the development of even more sophisticated and complex models that need to be optimized. Frequently, function evaluation is the result of a time-consuming simulation, often nonsmooth or subject to numerical noise, preventing the use of derivative-based methods. Thus, Derivative-free and Simulation Based Optimization have emerged as important domains in nonlinear optimization, attracting researchers and practitioners to the development and analysis of efficient and robust algorithms, able to tackle these challenging problems.
The present special issue appears on occasion of the 2nd Derivative-free Optimization Symposium, that will be held from 24-28 June 2024 at University of Padova, Italy, and intends to contribute for the advancement of the knowledge in this scientific domain. With a first edition held in 2022, at University of British Columbia, Canada, this series of meetings of single-track presentations intends to gather the Derivative-free Optimization community, promoting collaborations and the integration of new members.
Main topics include, but are not restricted to:
- Derivative-free Optimization
- Simulation-based Optimization
- Blackbox Optimization
- Software development
- Worst-case complexity analysis
- Multiobjective Derivative-free Optimization
- Global Derivative-free Optimization
- Large-scale Derivative-free Optimization
- Applications
