A Chaotic Sobol Sequence-based multi-objective evolutionary algorithm for optimal design and expansion of water networks

•A novel CS-MOSADE algorithm is developed and tested for WDN design problems.•CS-MOSADE algorithm converged faster than the MOSADE and NSGA-II algorithms.•Smaller spacing metric indicated better uniformity in the obtained solutions.•Large reductions in GHG emissions were achieved over the WDN servic...

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Published in:Sustainable cities and society Vol. 87; p. 104215
Main Authors: Sirsant, Swati, Hamouda, Mohamed A., Shaaban, Mostafa F., Al Bardan, Mayyada Salem
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.12.2022
Subjects:
Expansion
GHG emissions
Multi-objective optimization
Optimal pump scheduling
Reliability assessment
Water distribution networks
DE
NSGA-II
GAFO
LP
CERI
GHG
EPS
NFE
HV
MODE-CSFLA
MC
SAES-RBF
EA
Expansion
Water distribution networks
WDN
EF
SAMOHS
CNHV
CS-MOSADE
MOPSO
LCC
PSO
RSM
Clustered-NA-ACO
Optimal pump scheduling
EADC
NP
GHG emissions
Reliability assessment
NLP
QRS
RNSGA-II
MOGA
GA
FADE
NHV
MODE-SaE
RHV
CF
ESS
FORM
PA-DSS
IGD
MOSADE-DP
NYT
WOA
SADE
jDE
ACO
MO-ASMOCH
PVC-O
HA
Multi-objective optimization
MCS
DESAP
ISSN:2210-6707, 2210-6715
Online Access:Get full text
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Abstract •A novel CS-MOSADE algorithm is developed and tested for WDN design problems.•CS-MOSADE algorithm converged faster than the MOSADE and NSGA-II algorithms.•Smaller spacing metric indicated better uniformity in the obtained solutions.•Large reductions in GHG emissions were achieved over the WDN service life. The design of a water distribution network (WDN) is an optimization problem that is computationally challenging with conflicting objectives. This study offers an enhanced Chaotic Sobol Sequence-based Multi-Objective Self-Adaptive Differential Evolution (CS-MOSADE) algorithm for multi-objective WDN design. The CS-MOSADE algorithm was tested on two benchmark WDNs, and a real WDN. Optimization results indicate that the CS-MOSADE algorithm converged two to three times faster than the MOSADE and NSGA-IIalgorithms and led to better output in terms of even distribution of solutions and convergence towards the true Pareto-optimal front. Smaller spacing metric indicated better uniformity in the obtained solutions; and larger hyper-area and coverage function values depicted better convergence towards the true Pareto-optimal front for the CS-MOSADE algorithm compared to the other algorithms. The CS-MOSADE algorithm was then applied to solve a WDN expansion problem for optimal pump scheduling and minimization of Life Cycle Cost, maximization of reliability and minimization of Green House Gas (GHG) emissions. A significant reduction in GHG emissions of 2.17 x 106 kg was achieved at an additional cost of $0.55 x 107 when optimal pump scheduling was incorporated in the model of the real WDN over service life of 50 years.
AbstractList •A novel CS-MOSADE algorithm is developed and tested for WDN design problems.•CS-MOSADE algorithm converged faster than the MOSADE and NSGA-II algorithms.•Smaller spacing metric indicated better uniformity in the obtained solutions.•Large reductions in GHG emissions were achieved over the WDN service life. The design of a water distribution network (WDN) is an optimization problem that is computationally challenging with conflicting objectives. This study offers an enhanced Chaotic Sobol Sequence-based Multi-Objective Self-Adaptive Differential Evolution (CS-MOSADE) algorithm for multi-objective WDN design. The CS-MOSADE algorithm was tested on two benchmark WDNs, and a real WDN. Optimization results indicate that the CS-MOSADE algorithm converged two to three times faster than the MOSADE and NSGA-IIalgorithms and led to better output in terms of even distribution of solutions and convergence towards the true Pareto-optimal front. Smaller spacing metric indicated better uniformity in the obtained solutions; and larger hyper-area and coverage function values depicted better convergence towards the true Pareto-optimal front for the CS-MOSADE algorithm compared to the other algorithms. The CS-MOSADE algorithm was then applied to solve a WDN expansion problem for optimal pump scheduling and minimization of Life Cycle Cost, maximization of reliability and minimization of Green House Gas (GHG) emissions. A significant reduction in GHG emissions of 2.17 x 106 kg was achieved at an additional cost of $0.55 x 107 when optimal pump scheduling was incorporated in the model of the real WDN over service life of 50 years.
ArticleNumber 104215
Author Shaaban, Mostafa F.
Al Bardan, Mayyada Salem
Hamouda, Mohamed A.
Sirsant, Swati
Author_xml – sequence: 1
  givenname: Swati
  surname: Sirsant
  fullname: Sirsant, Swati
  organization: Department of Electrical Engineering, Faculty of Engineering, American University of Sharjah, Sharjah, United Arab Emirates
– sequence: 2
  givenname: Mohamed A.
  orcidid: 0000-0003-1797-4904
  surname: Hamouda
  fullname: Hamouda, Mohamed A.
  email: m.hamouda@uaeu.ac.ae
  organization: Department of Civil and Environmental Engineering, Faculty of Engineering, United Arab Emirates University, Al Ain, Abu Dhabi, United Arab Emirates
– sequence: 3
  givenname: Mostafa F.
  surname: Shaaban
  fullname: Shaaban, Mostafa F.
  organization: Department of Electrical Engineering, Faculty of Engineering, American University of Sharjah, Sharjah, United Arab Emirates
– sequence: 4
  givenname: Mayyada Salem
  surname: Al Bardan
  fullname: Al Bardan, Mayyada Salem
  organization: Research and Studies Department, Sharjah Electricity and Water Authority, Sharjah, United Arab Emirates
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Keywords DE
NSGA-II
GAFO
LP
CERI
GHG
EPS
NFE
HV
MODE-CSFLA
MC
SAES-RBF
EA
Expansion
Water distribution networks
WDN
EF
SAMOHS
CNHV
CS-MOSADE
MOPSO
LCC
PSO
RSM
Clustered-NA-ACO
Optimal pump scheduling
EADC
NP
GHG emissions
Reliability assessment
NLP
QRS
RNSGA-II
MOGA
GA
FADE
NHV
MODE-SaE
RHV
CF
ESS
FORM
PA-DSS
IGD
MOSADE-DP
NYT
WOA
SADE
jDE
ACO
MO-ASMOCH
PVC-O
HA
Multi-objective optimization
MCS
DESAP
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Snippet •A novel CS-MOSADE algorithm is developed and tested for WDN design problems.•CS-MOSADE algorithm converged faster than the MOSADE and NSGA-II...
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SubjectTerms Expansion
GHG emissions
Multi-objective optimization
Optimal pump scheduling
Reliability assessment
Water distribution networks
Title A Chaotic Sobol Sequence-based multi-objective evolutionary algorithm for optimal design and expansion of water networks
URI https://dx.doi.org/10.1016/j.scs.2022.104215
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