2013/05/08 by Matteo Giuliani, Andrea Castelletti · 1 citation
Engineering · Decision Sciences · Environmental Science · #Water resources management and optimization #Auction Theory and Applications #Water-Energy-Food Nexus Studies #Information exchange #Computer science #Upstream (networking) #Value of information #Value (mathematics) #Work (physics) #Downstream (manufacturing) #Decision maker #Operations research #Scale (ratio) #Perspective (graphical) #Environmental economics #Management science #Economics #Operations management #Engineering #Artificial intelligence
paper · pdf · doi:10.1002/wrcr.20287
openalex publication_date 2013/05/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
Many large‐scale water resources systems, especially in transboundary contexts, are characterized by the presence of several and conflicting interests and managed by multiple, institutionally independent decision makers. These systems are often studied adopting a centralized approach based on the assumption of full cooperation and information exchange among the involved parties. Such a perspective is conceptually interesting to quantify the best achievable performance but might have little practical impact given the real political and institutional setting. In this work, we propose a novel decision‐analytic framework based on multiagent systems to model and analyze different levels of cooperation and information exchange among multiple decision makers. The Zambezi River basin is used as a case study. According to the proposed agent‐based optimization approach, each agent represents a decision maker, whose decisions are defined by an explicit optimization problem considering only the agent's local interests. The economic value of information exchange is estimated comparing a noncooperative setting, where agents act independently, with the first basic level of cooperation, i.e., coordination, characterized by full information exchange. The economic value of cooperation is also estimated by comparison with the ideal, fully cooperative management of the system. Results show that coordination, obtained with complete information exchange, allows the downstream agents to better adapt to the upstream behaviors. The impact of information exchange depends on the objective considered, and we show coordination to be particularly beneficial to environmental interests.