I am using scenred (Gams) to apply scenario reduction for a stochastic LP model. I have 10800 scenarios. I have three uncertain parameters, two of them are in objective function and one of them is right hand side value. Two stage stochastic programming solution should be worse than the wait-and-see result which is the expected value of solutions obtained from all 10800 scenarios. But in my case, I found a stochastic programming solution better than wait-and-see. I know it is impossible but I couldn't figure out the problem in my model or code. I checked all probabilities, scenarios and tree. They all seem right. Also the Gams code dosen't give any error. Is there anyone using scenred tool of Gams and encounter similar problem before?
Hi,
Your question: The possible errors that cause better stochastic programming solution than wait-and-see solution. Kindly see the attachment, I think it would be very useful to you.
http://www.csee.wvu.edu/~xinl/library/books/stochastic_programming.pdf
There should be a problem with the constraints. I would definitely check the non-anticipativity contraints first.
Check the probability of each scenario, the summation of the probabilities should be equal to one, once, I made this mistake. Maybe you have made.
Hello,
Have you considered 'Nonanticipativity Constraints' in your stochastic programming model?
http://mortezash.blogfa.com/
Is your model a mixed-integer one, which could not be solved to optimality for at least some of the scenarios? The gaps could then possibly be a reason for the erroneous result. Or is it perhaps a nonconvex nonlinear model, where only local solutions were found, being inferior to the global solution?
Which format is your problem, could you share it?
Thank you for the answers. I found the problem. My model is a MIP model. The reason that wait-and-see solution is worse than stochastic programming solution is scenario reduction. I had compare the result of reduced scenarios (300 scenarios) with 10000 scenarios. That is why the comparison doesn't make sense.
- Badges
- Science topic