Nested algorithms for optimal reservoir operation and their embedding in a decision support platform

By Blagoj Delipetrev

The thesis presents novel algorithms for optimal reservoir operation, named nested DP (nDP), nested SDP (nSDP), nested reinforcement learning (nRL) and their multi-objective (MO) variants, correspondingly MOnDP, MOnSDP and MOnRL.
The idea is to include a nested optimization algorithm into each state transition, which reduces the initial problem dimension and alleviates the curse of dimensionality. These algorithms can solve multi-objective optimization problems, without significantly increasing the algorithm complexity or the computational expenses.
Nested optimization algorithms are embedded in a cloud application platform for water resources modeling and optimization. The platform is available 24/7, accessible from everywhere, scalable, distributed, interoperable, and it creates a real-time multiuser collaboration platform.

• Format: Hardcover
• Language: English
• ISBN: 113837346X
• ISBN13: 9781138373464
• Release Date: September 2018
• Publisher: CRC Press
• Length: 156 Pages
• Weight: 0.88 lbs.
• Dimensions: 0.4" x 6.1" x 9.2"