[SMI] INFORMS ICP Sessions on "Stability, Sample Size, and Smoothing Techniques for Stochastic Programming"

[Lijian Chen]

Apologies for cross-postings in advance. 

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Dear Friends and Colleagues,

I am invited to organize an ICS-sponsored session entitled "Stability, Sample Size, and Smoothing Techniques for Stochastic Programming" at the INFORMS annual meeting Nov 7-10 in Austin, Texas.

Topics may cover the most recent research topics on:

o Stability issues on Stochastic Programming under perturbations from structural/nonstructural/distributional parameters. 
o Smoothing techniques to overcome the non-differentiablity in stochastic programming and thereby install convex optimization.
o Practical method in reducing sample size required.
o Other practical methods addressing the computational challenges for large scale stochastic programming. 

As a junior faculty, it is my honor to serve the ICP-session and I would try my best to make the session productive. My goal of this session is to exchange research ideas and more importantly, develop sustainable collaborations. Any optimization researcher with great topics is encouraged to submit your abstract to me and join us during session. 

Please reply to this email so that I can move forward. BTW, have you completed the survey at 

http://www.uncertaintylab.com/survey

Thanks!!!



Sincerely Yours

Lijian Chen

Assistant Professor
Department of Industrial Engineering
J.B. Speed School of Engineering
University of Louisville
Louisville, KY 40292
http://www.uncertaintylab.com/
(Tel) 502-852-2197
(Fax) 502-852-5633