Linking Distributed Optimization Models for Food, Water, and Energy Security Nexus Management

Yuri Ermoliev, Anatolij G. Zagorodny, Vjacheslav L. Bogdanov, Tatiana Ermolieva, Peter Havlik, Elena Rovenskaya, Nadejda Komendantova and Michael Obersteiner
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Yuri Ermoliev: International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
Anatolij G. Zagorodny: Bogolyubov Institute for Theoretical Physics, National Academy of Sciences of Ukraine, 03142 Kiev, Ukraine
Vjacheslav L. Bogdanov: Timoshenko Institute of Mechanics, National Academy of Sciences of Ukraine, 03142 Kiev, Ukraine
Tatiana Ermolieva: International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
Elena Rovenskaya: International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
Nadejda Komendantova: International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
Michael Obersteiner: International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria

Sustainability, 2022, vol. 14, issue 3, 1-14

Abstract: Traditional integrated modeling (IM) is based on developing and aggregating all relevant (sub)models and data into a single integrated linear programming (LP) model. Unfortunately, this approach is not applicable for IM under asymmetric information (ASI), i.e., when “private” information regarding sectoral/regional models is not available, or it cannot be shared by modeling teams (sectoral agencies). The lack of common information about LP submodels makes LP methods inapplicable for integrated LP modeling. The aim of this paper is to develop a new approach to link and optimize distributed sectoral/regional optimization models, providing a means of decentralized cross-sectoral coordination in the situation of ASI. Thus, the linkage methodology enables the investigation of policies in interdependent systems in a “decentralized” fashion. For linkage, the sectoral/regional models do not need recoding or reprogramming. They also do not require additional data harmonization tasks. Instead, they solve their LP submodels independently and in parallel by a specific iterative subgradient algorithm for nonsmooth optimization. The submodels continue to be the same separate LP models. A social planner (regulatory agency) only needs to adjust the joint resource constraints to simple subgradient changes calculated by the algorithm. The approach enables more stable and resilient systems’ performance and resource allocation as compared to the independent policies designed by separate models without accounting for interdependencies. The paper illustrates the application of the methodology to link detailed energy and agricultural production planning models under joint constraints on water and land use.

Keywords: asymmetric information; linkage; nonsmooth optimization; subgradient; integrated modeling; food-energy-water-land nexus; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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