M. Giuliani, , Y. Li, A. Cominola, S. Denaro, E. Mason, A. Castelletti.

Water reservoir operations have great potential for contributing positively to the development of different socio-economic sectors as well as for reducing the vulnerabilities of water systems caused by changing hydroclimatic and anthropogenic forcing. This motivates the search for advanced, flexible, and open tools supporting the design of operating policies capable of meeting multiple competing objectives. This work contributes the Multi-Objective Optimal Operations (M3O) Matlab toolbox, which allows users to design Pareto optimal (or approximate) operating policies for managing water reservoir systems through several alternative state-of-the-art methods. Version 1.0 of M3O includes Deterministic and Stochastic Dynamic Programming, Implicit Stochastic Optimization, Sampling Stochastic Dynamic Programming, fitted Q-iteration, Evolutionary Multi-Objective Direct Policy Search, and Model Predictive Control. The toolbox is designed to be accessible to practitioners, researchers, and students, and to provide a fully commented and customizable code for more experienced users.

The study is available here.