Maximum entropy principle approach for water distribution network optimization

We propose a deterministic annealing (DA) framework, based on Jaynes’ maximum entropy principle, for simultaneous joint optimization of reservoir placement, network routing, and associated transport costs in water distribution networks (WDNs). Our approach leverages DA to decentralize WDNs, addressing the vulnerabilities of traditional centralized systems and reducing energy costs. We introduce a capacity-constrained formulation that limits the number of demand points served by each intermediate source point, thereby preventing overload and enhancing system stability. To enforce the resulting inequality constraints, we derive update rules for secondary Lagrange multipliers and analyze the sensitivity of the parameters. Finally, we extend the framework to utilize real-world pipe networks and validate our algorithm through a case study on the Modena, Italy network. Experimental results demonstrate that our DA-based method achieves lower operational costs and improved resilience compared to previous approaches.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Industrial Engineering

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Hong, Sungi

Contributors dc:contributor

• Beck, Carolyn

• Water Distribution Network
• Optimization
• Deterministic Annealing, Maximum Entropy Principle
• Facility Location

Statement dc:rights

• Copyright 2025 Sungi Hong

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129328

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129328