Bi-objective optimization of a water network via benchmarking

Tokos, Hella; Pintarič, Zorka Novak; Yang, Yongrong

doi:10.1016/j.jclepro.2012.07.051

Cited by 24 publications

(11 citation statements)

References 43 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…(2) Australian Countries The urban water utility sector in Australia has not always been the focus of government policy [33], [37], [39]. The first landmark document, 'A Water Resource Policy', dates from 1994 and was produced by the Council of Australian Governments (COAG).…”

Section: Performance Benchmarking Of Water Utilities -A Brief Summary Of Some Case Studiesmentioning

confidence: 99%

Performance Benchmarking of Water Supply Systems in Kandahar City using Data Envelopment Analysis (DEA)

Haziq¹,

Mosameem²,

Muslim³

et al. 2019

EJERS

View full text Add to dashboard Cite

Two Water Supply Systems (WSSs) have been operating and providing drinking water services to two discrete districts, namely, Second Ayno Maina (AM-WSS), District 10, owned and managed by a private sector: AFCO Corporation, and Central Kandahar (CK-WSS), Share-Naw, District 2, owned and managed by government entity: Department of Kandahar Water Supply and Sewerage, for four and ten years respectively. Both the WSSs use groundwater as source of drinking water, and due to overpopulation and urbanization, they tend to expand their services and improve their performances, despite the fact that the primary step to do so is the performance assessment of the existing systems, lacking at the moment and needs a careful consideration. Therefore, the research study is aimed at assisting the responsible authorities of the performances being carried by their existing systems and satisfaction level of their customers against the services provided, along with their international comparisons, with similar-typed associated water supply schemes. Two sets of primary data were collected, including service-provider-driven and customer-driven, from relevant authorities and districts respectively. More specifically, for consumer-driven data collection, 66 and 75 questionnaires were distributed to the consumers of (AM-WSS) and (CK-WSS) respectively. Both the data set was classified as the input and output performance indicators (PIs), and was analyzed using SPSS, DEAP and Ms. Excel softwares, in compliance with Data Envelopment Analysis (DEA) methodology. The findings showed that (AM-WSS) had a relative technical efficiency, te of 1 (100 %), whereas CK-WSS had a te of 0.545. As a result, CK-WSS was the only System considered and recommended for amendments. Furthermore, the analysis of the findings showed that CK-WSS needed to focus on decreasing the staff size and total expenditure by 45 % to comply with optimization. The team recommends to train their personnel and reduce the number by 45 %, and additionally recommends to collect, keep and register all the necessary data of the schemes in an organized manner for future demands, plans, rehabilitation, performance, and improvements of the corresponding components of their systems.

show abstract

Section: Performance Benchmarking Of Water Utilities -A Brief Summary Of Some Case Studiesmentioning

confidence: 99%

Performance Benchmarking of Water Supply Systems in Kandahar City using Data Envelopment Analysis (DEA)

Haziq¹,

Mosameem²,

Muslim³

et al. 2019

EJERS

View full text Add to dashboard Cite

show abstract

“…Isto significa que não é possível melhorar um dos objetivos sem piorar o outro. Portanto, o ponto crucial da otimização bi-objetivo é a obtenção da curva de troca entre esses dois tipos de objetivos (TOKOS et al, 2013).…”

Section: ____________________________________________________________unclassified

Redes Neurais Artificiais E Algoritmos Evolucionários Multipopulação Na Otimização Multiobjetivo Da Remediação De Águas Subterrâneas

et al. 2014

View full text Add to dashboard Cite

A groundwater remediation optimization problem through pump-and-treat technique is presented. Two objectives were pursued: 1) contaminant plume minimization; and 2) total cost minimization of remediation. Two multi-population evolutionary algorithms together with the artificial neural network (ANN) technology were employed in order to solve this problem. Pump rates from wells were sent to ANN that computes the remained contaminant mass left in the site. The ANN outcomes were sent to evolutionary algorithms to execute optimization process.

show abstract

“…For the regeneration recycling water networks, the design methods can be classified into water pinch methods (such as Wang and Smith, 1994), mathematical programming methods (such as Tokos et al, 2013) and heuristic methods (such as Liu et al, 2009a,b).…”

Section: Introductionmentioning

confidence: 99%

“…The objective function can be the freshwater flow rate (Faria et al, 2009;Tokos and Pintari c, 2009;Boix et al, 2012), the regeneration flow rate (Deng et al, 2013), or the total cost (Feng and Chu, 2004;Tokos et al, 2013). By using mathematical programming formulations, such as mixed-integer linear programming (MILP) (Bagajewicz and Savelski, 2001) and mixedinteger nonlinear programming (MINLP) (N apoles-Rivera et al, 2015), the mathematical model can be solved and the design of water networks can be obtained.…”

Section: Introductionmentioning

confidence: 99%

Design of regeneration recycling water networks by means of concentration potentials and a linear programming method

Zhao

Wang

Chan

et al. 2016

Journal of Cleaner Production

View full text Add to dashboard Cite

Bi-objective optimization of a water network via benchmarking

Cited by 24 publications

References 43 publications

Performance Benchmarking of Water Supply Systems in Kandahar City using Data Envelopment Analysis (DEA)

Performance Benchmarking of Water Supply Systems in Kandahar City using Data Envelopment Analysis (DEA)

Redes Neurais Artificiais E Algoritmos Evolucionários Multipopulação Na Otimização Multiobjetivo Da Remediação De Águas Subterrâneas

Design of regeneration recycling water networks by means of concentration potentials and a linear programming method

Contact Info

Product

Resources

About