Derivative-Free Hybrid Optimization Methods for Solving Simulation-Based Problems in Hydrology
October 6 to October 10, 2008
American Institute of Mathematics,
Palo Alto, California
and Genetha Gray
This workshop will bring together researchers with expertise in simulation-based optimization, sampling techniques, optimization using surrogates, and hydrology to tackle the complex issues that arise in water resources management applications. For example, plume containment, water supply, and parameter estimation
problems rely on optimization algorithms working in conjunction with subsurface simulation tools. The inherent challenges, which are in fact present across all engineering disciplines, include black-box, nonlinear objective functions and constraints, and non-convex, disconnected feasible regions. Hybrid optimization methods offer a potential solution to these problems, but require a deeper analysis to understand their applicability.
Our interests are in
- the development and analysis of hybrid optimization methods to improve accuracy, efficiency and reliability of solutions for this class of problems and to exploit the strengths of a variety of derivative-free optimization and sampling methods not commonly used in hydrology,
- understanding how to choose appropriate algorithms for a specific type of problem, which involves a classification of both problem types and hybrid approaches,
- developing metrics to compare hybrid algorithms, and study these comparisons on benchmarking problems from hydrology.
Material from the workshop
A list of participants.
The workshop schedule.
A report on the workshop activities.
Papers arising from the workshop: