Enhancing Sustainability and Efficiency in Water Distribution Systems through Mathematical Optimization And AI

Abstract

Efficient and sustainable management of water distribution systems (WDS) is a pressing challenge in modern urban planning and infrastructure development. This research explores the integration of mathematical optimization techniques and artificial neural networks (ANNs) in improving the operational efficiency and sustainability of WDS. By leveraging optimization models for resource allocation and ANN-based predictive analytics, this study provides a framework for reducing energy consumption, minimizing water loss, and ensuring equitable water distribution. Key applications, case studies, and future research directions are discussed, underscoring the transformative potential of these technologies in addressing global water management challenges.