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eISSN: 2083-5906
ISSN: 1230-1485
ISSN: 1230-1485
ORIGINAL RESEARCH
Urban Water-Planning Support System
Using Fuzzy Logic and Metaheuristic
Algorithms Under Sustainability Criteria
1
Dirección de Investigación, Innovación y Posgrado, Universidad Politécnica de Pachuca, Carretera Pachuca – Cd.
Sahagún Km 20, Ex-Hacienda de Santa Bárbara, Zempoala, HGO, 43830, México
2
Universidad Politécnica Metropolitana de Hidalgo, Ex Hacienda San Javier, Tolcayuca 1009, Tolcayuca,
HGO, 43860, México
Submission date: 2025-06-21
Final revision date: 2025-11-13
Acceptance date: 2026-01-07
Online publication date: 2026-03-04
Corresponding author
Jorge A. Ruiz-Vanoye
Dirección de Investigación, Innovación y Posgrado, Universidad Politécnica de Pachuca, Carretera Pachuca – Cd. Sahagún Km 20, Ex-Hacienda de Santa Bárbara, Zempoala, HGO, 43830, México
Dirección de Investigación, Innovación y Posgrado, Universidad Politécnica de Pachuca, Carretera Pachuca – Cd. Sahagún Km 20, Ex-Hacienda de Santa Bárbara, Zempoala, HGO, 43830, México
KEYWORDS
water optimisationsmart citiessustainable water managementurban water systemsresource efficiencyfuzzy logicgenetic algorithm
TOPICS
ABSTRACT
This article presents the development and implementation of an urban water planning decisionsupport
system that integrates fuzzy logic techniques and a set of 25 metaheuristic algorithms.
The model is designed to operate under an environment characterised by multiple operational,
environmental, regulatory, and infrastructure constraints, which are incorporated through dynamic
penalties in the objective function. Fuzzy logic is used to transform imprecise critical variables, such
as source availability, sectoral demands, and operating costs, into CRISP inputs usable by optimisation
algorithms. The methodology allows for the evaluation and comparison of the performance of each
heuristic in terms of computational efficiency, solution quality, and feasibility under realistic urban
conditions. The results show significant differences in accuracy, robustness, and convergence times,
providing a quantitative basis for the selection of sustainable, resilient, and adaptive water management
strategies in the context of smart cities. Finally, future lines of research are proposed, focusing on
algorithmic hybridisation, the incorporation of Explainable Artificial Intelligence (XAI), and integration
with real-time water governance platforms.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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