Blog 8

Neural Network-Based Simulation-Optimization Model for Reservoir Operation
By T.R. Neelakantan and N.V. Pundarikanthan

Summary

In many reservoir operations studies - such as that of Chennai, India, which is the case used for this article – complex simulation models combined with optimization models are computationally infeasible when trying to model the problem. In an effort to circumvent this problem, the authors propose a way to develop a “planning model for reservoir operation that uses a simulation-optimization approach.” To do this they use a neural network-based simulation model, which was developed for reservoir system operation, as a submodel in a Hooke and Jeeves unconstrained nonlinear programming model. The optimization model minimized the operation policies.
That’s it in a nutshell… if you want more you’ll have to wait until Wednesday when Michelle and I present. The suspense is killing you I’m sure.

Discussion

I thought this article was a little more difficult to follow than the previous few articles. Or it could be that I’m already creating excuses for why I might be clueless come Wednesday.  Either way, I still don’t feel I have a great grasp on all the terms and concepts explained in the paper. In particular, I don’t really understand how the exemplars are selected or how a neural network simulation model is formed.