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Neural network-informed Optimal Water Flow problem: Modeling, algorithm, and benchmarking

delete2026-01-12
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OA
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A
A. Belmondo Bianchi *
H
H.H.M. Rijnaarts
S
S. Shariat Torbaghan
DOI：10.1016/j.wroa.2025.100479delete
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Abstract

Abstract

En 中文
• Proposes a new method for solving the Optimal Water Flow problem. • Uses a neural network to approximate nonconvex constraints. • Introduces a loss regularization scheme to enforce convexity. • Reformulates the inference problem as a linear program. • Benchmarks the method against standard models to show its benefits.
Keywords:
Water distribution network
Mathematical optimization
Input convex neural network
Water–energy nexus
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

W
Water Research X
IF:
8.2
Papers:
185
Citations:
0

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No organization information available