A deep learning-based robust optimization approach for refinery planning under uncertainty.
Cong WangXin PengChao ShangChen FanLiang ZhaoWeimin ZhongPublished in: Comput. Chem. Eng. (2021)
Keyphrases
- deep learning
- robust optimization
- planning under uncertainty
- decision theoretic
- unsupervised learning
- markov decision processes
- mathematical programming
- ai planning
- dynamical systems
- machine learning
- multi agent
- decision theory
- partially observable markov decision processes
- mental models
- lot sizing
- weakly supervised
- semidefinite programming
- finite state
- planning problems
- probability distribution
- feature extraction
- decision making