Come join ISE’s faculty and fellow students as they welcome Susan Hunter, associate professor, from Purdue as she discusses bi-objective simulation optimization on integer lattices.
As always refreshments will be served from 10:30 – 10:50 am in room 428 Daniels Hall.
We propose the Retrospective Partitioned Epsilon-constraint with Relaxed Local Enumeration (R-PERLE)algorithm to solve the bi-objective simulation optimization problem on integer lattices. In this nonlinear optimization problem, both objectives can only be observed with stochastic error, the decision variables are integer-valued, and a local solution is called a local efficient set. R-PERLE employs a version of sample average approximation called retrospective approximation (RA) to repeatedly call the PERLEsample-path solver at a sequence of increasing sample sizes, using the solution from the previous RA iteration as a warm start for the current RA iteration. As the number of RA iterations increases, R-PERLEprovably converges to a local efficient set with probability one under appropriate regularity conditions. We discuss the design principles that make our algorithm efficient and demonstrate that R-PERLEperforms favorably relative to the current state of the art, MO-COMPASS, in our numerical experiments.
This work is joint with Kyle Cooper and Kalyani Nagaraj. A preprint of the paper, forthcoming inINFORMS Journal on Computing, is available at:
http://www.optimization-online.org/DB_HTML/2018/06/6649.html
The algorithms in the above paper have subsequently been incorporated into Python software called PyMOSO, which is available for download from PyPI. A preprint of the software paper, also forthcoming in INFORMS Journal on Computing, is available at:
http://www.optimization-online.org/DB_HTML/2018/10/6876.html
Susan R. Hunter is an assistant professor in the School of Industrial Engineering at PurdueUniversity. She received her Ph.D. in 2011 from the Grado Department of Industrial and systems engineering at Virginia Tech and was a postdoctoral associate in the School of Operations Research and Infomation Engineering at Cornell University from 2011 to 2013. Her primary research area is multi-objective simulation optimization, a topic for which she received an NSF CAREER award in 2016. More information is available on her website:
http://web.ics.purdue.edu/~hunter63/
