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Computational Experience with Asynchronous Projective Hedging

June 12, 2018, 4:10 PM - 4:40 PM



Rutgers University

CoRE Building

96 Frelinghuysen Road

Piscataway, NJ 08854

Click here for map.

David L. Woodruff, University of California, Davis

Recent work by Eckstein and Combettes resulted in development of an algorithm for multi-stage, convex stochastic optimization problems with uncertain input data expressed as a set of scenarios. The algorithm is called Asynchronous Projective Hedging (APH). In this talk we describe computational experience with this algorithm primarily based on two well-known problems from the stochastic programming literature: saphir and ssn. We explore various tradeoffs such as computational resources vs. wall-clock vs. solution quality as well primal versus dual solution quality.

Co-authors: Jonathan Eckstein, Rutgers and Jean-Paul Watson, Sandia








Slides    Video