Max-affine estimators for convex stochastic programming.
2016
In this paper, we consider two sequential decision making problems with a convexity structure, namely an energy storage optimization task and a multi-product assembly example. We formulate these problems in the stochastic programming framework and discuss an approximate dynamic programming technique for their solutions. As the cost-to-go functions are convex in these cases, we use max-affine estimates for their approximations. To train such a max-affine estimate, we provide a new convex regression algorithm, and evaluate it empirically for these planning scenarios.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
15
References
1
Citations
NaN
KQI