CV


FA
Hadi Mokhtari

Hadi Mokhtari

Associate Professor

College: Faculty of Engineering

Department: Industrial Engineering

Degree: Ph.D

CV
FA
Hadi Mokhtari

Associate Professor Hadi Mokhtari

College: Faculty of Engineering - Department: Industrial Engineering Degree: Ph.D |

Optimizing water sustainability: integrating blockchain technology in the water and wastewater supply chain management

Authorsهادی مختاری,سعید دهنوی آرانی
JournalOperational Research
Page number39
Volume number26
IFثبت نشده
Paper TypeFull Paper
Published At2026-03-16
Journal GradeScientific - research
Journal TypeElectronic
Journal CountryIran, Islamic Republic Of
Journal IndexJCR ,SCOPUS
KeywordsSupply chain design · Water distribution · Wastewater collection · Blockchain technology · Mathematical optimization

Abstract

The water and wastewater supply chain plays a pivotal role in promoting sustainability by ensuring access to clean water for diverse applications while effectively managing wastewater to mitigate environmental pollution. Efficient management of this supply chain is essential for conserving water resources, protecting ecosystems, and improving public health. Optimizing key processes such as treatment, distribution, and recycling can significantly reduce water losses and energy consumption. In this context, blockchain technology emerges as a promising solution to enhance transparency, traceability, and operational efficiency by securely recording transactions and data flows. However, blockchain adoption also entails operational energy use, social impacts, and fixed infrastructure costs that must be carefully balanced against its potential benefits. This study proposes a comprehensive water and wastewater supply chain framework incorporating dams, groundwater and surface water sources, treatment plants, reservoirs, demand zones, recycling collection centers, and industrial users. Water is collected from multiple sources, treated, stored, distributed to consumers, and subsequently collected for recycling and industrial reuse. To support optimal network design, a mixed-integer linear programming model is developed and validated through an illustrative case study.