[Coin-discuss] questions on SMI

[Brady Hunsaker]

I'm currently sitting in on a course on stochastic programming.  There
are about a dozen Ph.D. students in the class, all of whom must do some
computational exercises (such as implementing the L-shaped method) as
well as a final project.  If I act fast I may be able to convince one or
more of them to do final projects that also contribute to SMI.

However, I'm having a little trouble understanding what SMI can already
do and what it aspires to.  I've been looking through the documentation
and code, including the unitTest code.

I'd appreciate it if someone familiar with SMI could answer these few
questions:

1.  Current capabilities of SMI:  store scenario-based problems, read
SMPS format, use OSI to solve deterministic equivalent (extensive
form).  Is that correct?  

2.  Would an L-shaped method algorithm be a good addition?  Is one
already in the works?  Are other solution methods particularly desirable
at this point?

3.  Is it correct that adding chance constraints would involve
developing a new class?  (For starters, I guess it would store the
description of the chance constraints and would also provide a solution
through deterministic equivalents for the basic cases.)  

4.  Any other ideas for projects that might be useful at this point?

Students are supposed to decide their final project topics by the end of
the week, so a response within a day or two would be appreciated. 
Thanks,

Brady

-- 
Brady Hunsaker
Assistant Professor
Industrial Engineering
University of Pittsburgh
http://www.engr.pitt.edu/hunsaker/