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

TL;DR

This paper presents nested algorithms for reservoir operation optimization, including dynamic programming, stochastic dynamic programming, and reinforcement learning, with multi-objective extensions, integrated into a decision support platform.

Contribution

It introduces nested versions of key optimization algorithms and their multi-objective variants, embedded within a decision support system for reservoir management.

Findings

Effective optimization of reservoir operations demonstrated

Multi-objective algorithms handle trade-offs between conflicting goals

Algorithms integrated into a practical decision support platform

Abstract

This is a PhD thesis of Blagoj Delipetrev explaining nested dynamic programming, nested stochastic dynamic programming and nested reinforcement learning algorithms that are applied in reservoir optimization problem. Additionally there are also multi-objective version of these algorithms.