Maximizing failure occurrence in water distribution Systems: A Multi-Objective approach considering Reliability, Economic, and environmental aspects

IF 7.5 1区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Expert Systems with Applications Pub Date : 2024-11-26 DOI:10.1016/j.eswa.2024.125910
Omid Abdolazimi , Mitra Salehi Esfandarani , Hadi Mazruee Kashani , Nazli Aghashahi
{"title":"Maximizing failure occurrence in water distribution Systems: A Multi-Objective approach considering Reliability, Economic, and environmental aspects","authors":"Omid Abdolazimi ,&nbsp;Mitra Salehi Esfandarani ,&nbsp;Hadi Mazruee Kashani ,&nbsp;Nazli Aghashahi","doi":"10.1016/j.eswa.2024.125910","DOIUrl":null,"url":null,"abstract":"<div><div>National and local regulations mandate water utilities to deliver safe and clean drinking water to consumers. However, due to the aging water infrastructure, they face numerous challenges regarding water loss and water quality impairments within the distribution networks. In this paper, a multi-objective nonlinear model was developed to maximize the buried water mean time to failure with consideration of cost and environmental aspects. The model determined the type of pipe material appropriate for each location with the maximum reliability, minimum environmental impacts, and minimum cost. An exact method (weighted sum method (WSM)) and two <em>meta</em>-heuristic algorithms (multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II)) were applied to solve the model in the large dimension. After examining the proposed solution methods across different numerical examples, the best optimal approach was identified. Then, the mathematical model and the best solution approach were validated in a real case study of the drinking water distribution system (WDS) in Iran. Moreover, the inherent uncertainty associated with the total cost objective function were assessed by conducting a sensitivity analysis on key parameters such as the annual interest rate, pipe cost, probability of pipe installation, and installation cost. Therefore, to overcome these uncertainties, a robust optimization method introduced by Soyster was used. Ultimately, the study provided managerial insights drawn from the results of the sensitivity analysis. The findings can aid water utilities and decision-makers in formulating water infrastructure rehabilitation plans that are more effective and characterized by diminished environmental impacts and lower costs.</div></div>","PeriodicalId":50461,"journal":{"name":"Expert Systems with Applications","volume":"264 ","pages":"Article 125910"},"PeriodicalIF":7.5000,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Systems with Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957417424027775","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

National and local regulations mandate water utilities to deliver safe and clean drinking water to consumers. However, due to the aging water infrastructure, they face numerous challenges regarding water loss and water quality impairments within the distribution networks. In this paper, a multi-objective nonlinear model was developed to maximize the buried water mean time to failure with consideration of cost and environmental aspects. The model determined the type of pipe material appropriate for each location with the maximum reliability, minimum environmental impacts, and minimum cost. An exact method (weighted sum method (WSM)) and two meta-heuristic algorithms (multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II)) were applied to solve the model in the large dimension. After examining the proposed solution methods across different numerical examples, the best optimal approach was identified. Then, the mathematical model and the best solution approach were validated in a real case study of the drinking water distribution system (WDS) in Iran. Moreover, the inherent uncertainty associated with the total cost objective function were assessed by conducting a sensitivity analysis on key parameters such as the annual interest rate, pipe cost, probability of pipe installation, and installation cost. Therefore, to overcome these uncertainties, a robust optimization method introduced by Soyster was used. Ultimately, the study provided managerial insights drawn from the results of the sensitivity analysis. The findings can aid water utilities and decision-makers in formulating water infrastructure rehabilitation plans that are more effective and characterized by diminished environmental impacts and lower costs.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
最大化配水系统的故障发生率:考虑可靠性、经济性和环境因素的多目标方法
国家和地方法规要求供水公司向消费者提供安全清洁的饮用水。然而,由于供水基础设施老化,供水公司面临着配水管网内水流失和水质受损的诸多挑战。本文开发了一个多目标非线性模型,在考虑成本和环境因素的情况下,最大限度地延长埋地水管的平均故障时间。该模型确定了适合每个地点的管道材料类型,同时兼顾最大可靠性、最小环境影响和最低成本。精确法(加权和法(WSM))和两种元启发式算法(多目标粒子群优化法(MOPSO)和非支配排序遗传算法 II(NSGA-II))被用于求解大维度模型。在对不同数值示例中的拟议求解方法进行研究后,确定了最佳优化方法。然后,在伊朗饮用水分配系统(WDS)的实际案例研究中对数学模型和最佳求解方法进行了验证。此外,通过对年利率、管道成本、管道安装概率和安装成本等关键参数进行敏感性分析,评估了与总成本目标函数相关的内在不确定性。因此,为了克服这些不确定性,采用了 Soyster 提出的稳健优化方法。最终,该研究从敏感性分析结果中获得了管理启示。研究结果可帮助水务公司和决策者制定更有效、对环境影响更小和成本更低的水基础设施修复计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Expert Systems with Applications
Expert Systems with Applications 工程技术-工程:电子与电气
CiteScore
13.80
自引率
10.60%
发文量
2045
审稿时长
8.7 months
期刊介绍: Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.
期刊最新文献
Joint optimization of quality control and maintenance policy for a production system with quality-dependent failures Consensus reaching for large-scale group decision making: A gain-loss analysis perspective Relation enhancement for noise resistance in open-world link prediction A coupled UAU-DKD-SIQS model considering partial and complete mapping relationship in time-varying multiplex networks Traffic prediction by graph transformer embedded with subgraphs
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1