Derivative Free and Black Box Optimization (17rit681)

The Banff International Research Station will host the "Derivative Free and Black Box Optimization" workshop in Banff from STARTDATE to ENDDATE.

Optimization, the study of minimizing or maximizing a function, arises naturally in almost every field of research. Applications can be found in everything from business (e.g., minimizing cost and maximizing profit) to engineering (e.g., maximizing structural integrity and minimizing hospital wait times). Many modern optimization applications take the form of determining the minimum (or maximum) of a function that is provided via a "black-box". The black-box is capable of providing a value for the input at a given point, but no other information. Research that relies on computer simulation typically falls into this category. Moreover, classical approaches (such as setting a "derivative" to 0) cannot be applied in such situations.

Derivative-free optimization (DFO) designs computer algorithms to solve such problems, studies convergence, and solves real-world applications of such problems. DFO is very young as a research field, but has made massive advances over the past decade and represent one of the most rapidly expanding fields of nonlinear optimization research. The foundational concepts in DFO have become sufficiently mature that it is now possible to teach them at a senior undergraduate level. In this project, we finalize details in a new book on "Derivative-Free and Blackbox Optimization", and make novel advances in the design of derivative-free optimization algorithms the merge direct-search and model-based techniques.

The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).