bibtype J - Journal Article
ARLID 0542604
utime 20230418204036.6
mtime 20210521235959.9
SCOPUS 85098650410
WOS 000604476100001
DOI 10.1007/s11269-020-02720-3
title (primary) (eng) Water Quality Sensor Placement: A Multi-Objective and Multi-Criteria Approach
specification
page_count 17 s.
media_type P
serial
ARLID cav_un_epca*0256041
ISSN 0920-4741
title Water Resources Management
volume_id 35
volume 1 (2021)
page_num 225-241
publisher
name Springer
keyword ELECTRE TRI
keyword Optimization
keyword Water distribution systems
keyword Water quality sensor placement
author (primary)
ARLID cav_un_auth*0409525
name1 Brentan
name2 B.
country BR
author
ARLID cav_un_auth*0398866
name1 Carpitella
name2 Silvia
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
country IT
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0409526
name1 Barros
name2 D.
country BR
author
ARLID cav_un_auth*0409527
name1 Meirelles
name2 G.
country BR
author
ARLID cav_un_auth*0399068
name1 Certa
name2 A.
country IT
author
ARLID cav_un_auth*0256480
name1 Izquierdo
name2 J.
country ES
source
url http://library.utia.cas.cz/separaty/2021/MTR/carpitella-0542604.pdf
source
url https://link.springer.com/article/10.1007/s11269-020-02720-3
cas_special
abstract (eng) To satisfy their main goal, namely providing quality water to consumers, water distribution networks (WDNs) need to be suitably monitored. Only well designed and reliable monitoring data enables WDN managers to make sound decisions on their systems. In this belief, water utilities worldwide have invested in monitoring and data acquisition systems. However, good monitoring needs optimal sensor placement and presents a multi-objective problem where cost and quality are conflicting objectives (among others). In this paper, we address the solution to this multi-objective problem by integrating quality simulations using EPANET-MSX, with two optimization techniques. First, multi-objective optimization is used to build a Pareto front of non-dominated solutions relating contamination detection time and detection probability with cost. To assist decision makers with the selection of an optimal solution that provides the best trade-off for their utility, a multi-criteria decision-making technique is then used with a twofold objective: 1) to cluster Pareto solutions according to network sensitivity and entropy as evaluation parameters. and 2) to rank the solutions within each cluster to provide deeper insight into the problem when considering the utility perspectives.The clustering process, which considers features related to water utility needs and available information, helps decision makers select reliable and useful solutions from the Pareto front. Thus, while several works on sensor placement stop at multi-objective optimization, this work goes a step further and provides a reduced and simplified Pareto front where optimal solutions are highlighted. The proposed methodology uses the NSGA-II algorithm to solve the optimization problem, and clustering is performed through ELECTRE TRI. The developed methodology is applied to a very well-known benchmarking WDN, for which the usefulness of the approach is shown. The final results, which correspond to four optimal solution clusters, are useful for decision makers during the planning and development of projects on networks of quality sensors. The obtained clusters exhibit distinctive features, opening ways for a final project to prioritize the most convenient solution, with the assurance of implementing a Pareto-optimal solution.
result_subspec WOS
RIV JN
FORD0 20000
FORD1 20500
FORD2 20501
reportyear 2022
num_of_auth 6
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0320681
confidential S
mrcbC86 1* Article Engineering Civil|Water Resources
mrcbC91 C
mrcbT16-e ENGINEERINGCIVIL|WATERRESOURCES
mrcbT16-j 0.636
mrcbT16-s 0.929
mrcbT16-D Q3
mrcbT16-E Q2
arlyear 2021
mrcbU14 85098650410 SCOPUS
mrcbU24 PUBMED
mrcbU34 000604476100001 WOS
mrcbU63 cav_un_epca*0256041 Water Resources Management 0920-4741 1573-1650 Roč. 35 č. 1 2021 225 241 Springer