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The University of Southampton
CORMSIS Centre for Operational Research, Management Sciences and Information Systems

"Equipment Designs for Inverse Approximations" - Professor Russell Barton (Penn State University) Event

Time:
14:00 - 15:00
Date:
21 November 2019
Venue:
Room 3023 (L/R F1), Building 7, University of Southampton, Highfield Campus, SO17 1BJ

For more information regarding this event, please email Christine Currie at C.S.M.Currie@southampton.ac.uk .

Event details

Many simulation-based design optimization scenarios are driven by an underlying inverse problem. Rather than iteratively exercise the (computationally expensive) simulation to find a suitable design (i.e., match a target performance vector), one might instead iteratively exercise the simulation to fit an inverse approximation, and use the approximation to indicate designs meeting multivariate performance targets. This talk examines issues in defining optimal designs for fitting inverse approximations. This work is joint with Max Morris, Iowa State University.

Speaker information

Professor Russell Barton , Penn State University, Distinguished Professor of Supply Chain and Information Systems in the Smeal College of Business at Penn State. He is currently Visiting Professor at the Durham University Business School, and he holds a courtesy appointment in the Department of Industrial and Manufacturing Engineering at Penn State. He is past Vice President, INFORMS Sections and Societies, and served on the INFORMS Analytics Certification Board. From 2010-2012 was Program Director for Manufacturing Enterprise Systems and Service Enterprise Systems at the U. S. National Science Foundation. He holds a B.S. in electrical engineering from Princeton University, and M.S. and Ph.D. degrees in operations research from Cornell University. He is a Fellow of IISE, a Certified Analytics Professional, and Senior Member of IEEE. He serves on the editorial boards of Operations Research and the IMA Journal of Management Mathematics. His research has focused on the interface between applied statistics, simulation, and product design and manufacturing.

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