A comprehensive criteria-based multi-attribute decision-making model for rehabilitation of water distribution systems

A comprehensive criteria-based multi-attribute decision-making model for rehabilitation of water distribution systems
复制标题

DOI:
10.1080/15732479.2017.1359633
复制
发表时间:
2018-01-01
影响因子:
3.7
通讯作者:
Tabesh, Massoud
Tabesh, Massoud
中科院分区:
工程技术3区
文献类型:
--
作者:
Salehi, Sattar;Ghazizadeh, Mohammadreza Jalili;Tabesh, Massoud

文献摘要

被引文献

相似文献

这项工作的主要目标是开发一个基于综合标准的多属性决策模型来规划水管网的修复。该模型的主要特点是能够同时分析供水网络修复的综合标准;运营数据存在重大不确定性。该模型称为WDSR模型,采用模糊TOPSIS技术,可以因地制宜地调整标准,并根据专家的群体决策进行加权。本文利用WDSR模型,通过两种方法对Anytown供水网络的修复计划进行优先级排序。第一种方法使用预定义的 WDSR 模板,第二种方法使用基于研究区域内条件的本地模板。获得的结果显示了 WDSR 在水管网修复规划中的潜力,该规划面临着众多标准、记录数据的显着不确定性以及专家群体决策的犹豫。研究发现,对于网络区域的修复,首选 WDSR 的预定义模板,而对于管道修复,则必须使用本地模板层。
The main objective of this work is to develop a comprehensive criteria-based multi-attribute decision-making model to plan the rehabilitation of water networks. Among the main features of this model is the capability to simultaneously analyse comprehensive criteria for the rehabilitation of water networks; where there is a significant uncertainty within the operational data. In this model, which is called as WDSR model, using a fuzzy TOPSIS technique, it is possible to adjust the criteria based on the local conditions, and to weight them based on the group decision-making of experts. In this paper, using the WDSR model, the rehabilitation plan of the Anytown' water network is prioritised through two methods. The first method uses a predefined template of WDSR, and the second uses a local template based on the conditions within the study area. The obtained results show the potential of the WDSR in the rehabilitation planning of water networks, where is encountered with numerous criteria, a significant uncertainty in the recorded data and hesitation in group decision-making of experts. It was found that, for rehabilitation of network zones, predefined template of WDSR is preferred, while for pipe rehabilitation, it is essential to use local template layer.