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I nfrastructure M odels : Composable Multi-infrastructure Optimization in Julia

Author

Listed:
  • Russell Bent

    (Los Alamos National Laboratory, Los Alamos, New Mexico 87545)

  • Byron Tasseff

    (Los Alamos National Laboratory, Los Alamos, New Mexico 87545)

  • Carleton Coffrin

    (Los Alamos National Laboratory, Los Alamos, New Mexico 87545)

Abstract

In recent years, there has been an increasing need to understand the complex interdependencies between critical infrastructure systems, for example, electric power, natural gas, and potable water. Whereas open-source and commercial tools for the independent simulation of these systems are well established, frameworks for cosimulation with other systems are nascent and tools for co-optimization are scarce—the major challenge being the hidden combinatorics that arise when connecting multiple-infrastructure system models. Building toward a comprehensive solution for modeling interdependent infrastructure systems, this work presents I nfrastructure M odels , an extensible, open-source mathematical programming framework for co-optimizing multiple interdependent infrastructures. This work provides new insights into methods and programming abstractions that make state-of-the-art independent infrastructure models composable with minimal additional effort. To that end, this paper presents the design of the I nfrastructure M odels framework, documents key components of the software’s implementation, and demonstrates its effectiveness with three case studies on canonical co-optimization tasks arising in interdependent infrastructure systems.

Suggested Citation

  • Russell Bent & Byron Tasseff & Carleton Coffrin, 2024. "I nfrastructure M odels : Composable Multi-infrastructure Optimization in Julia," INFORMS Journal on Computing, INFORMS, vol. 36(2), pages 600-615, March.
  • Handle: RePEc:inm:orijoc:v:36:y:2024:i:2:p:600-615
    DOI: 10.1287/ijoc.2022.0118
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    References listed on IDEAS

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    1. Conrado Borraz-Sánchez & Russell Bent & Scott Backhaus & Hassan Hijazi & Pascal Van Hentenryck, 2016. "Convex Relaxations for Gas Expansion Planning," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 645-656, November.
    2. Vieira, Bruno S. & Mayerle, Sérgio F. & Campos, Lucila M.S. & Coelho, Leandro C., 2020. "Optimizing drinking water distribution system operations," European Journal of Operational Research, Elsevier, vol. 280(3), pages 1035-1050.
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