Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties

Laurence W. Cook, Jerome P. Jarrett, Karen E. Willcox
  • January 2017, American Institute of Aeronautics and Astronautics (AIAA)
  • DOI: 10.2514/6.2017-0590

Optimization with probabilistic, interval and mixed uncertainties

What is it about?

Horsetail matching is a flexible approach for solving optimization under uncertainty problems. It can easily handle problems with probabilistic uncertainties, interval uncertainties, and mixed (both probabilistic and interval together) uncertainties.

Why is it important?

Accounting for uncertainty is critical in design of engineering systems. There are many different types of uncertainty that affect system performance and reliability. Most existing methods are restrictive in the types of uncertainty that can be handled. Horsetail matching overcomes this challenge.

The following have contributed to this page: Prof Karen E Willcox