Population size influence on the efficiency of evolutionary algorithms to design water networks

[EN] The optimal sizing in water distribution networks (WDN) is of great interest because it allows the selection of alternative economical solutions that ensure design requirements at nodes (demands and pressure) and at lines (velocities). Among all the available design methodologies, this work ana...

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Autores: Mora-Melia, Daniel, Gutiérrez-Bahamondes, Jimmy H., Martínez-Solano, F. Javier|||0000-0002-8140-5960, Iglesias Rey, Pedro Luís|||0000-0001-8300-3255
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/108644
Acceso en línea:https://riunet.upv.es/handle/10251/108644
Access Level:acceso abierto
Palabra clave:Water Distribution Systems
Design
Efficiency
Evolutionary Algorithms
MECANICA DE FLUIDOS
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repository_id_str
spelling Population size influence on the efficiency of evolutionary algorithms to design water networksMora-Melia, DanielGutiérrez-Bahamondes, Jimmy H.Martínez-Solano, F. Javier|||0000-0002-8140-5960Iglesias Rey, Pedro Luís|||0000-0001-8300-3255Water Distribution SystemsDesignEfficiencyEvolutionary AlgorithmsMECANICA DE FLUIDOS[EN] The optimal sizing in water distribution networks (WDN) is of great interest because it allows the selection of alternative economical solutions that ensure design requirements at nodes (demands and pressure) and at lines (velocities). Among all the available design methodologies, this work analyzes those based on evolutionary algorithms (EAs). EAs are a combination of deterministic and random approaches, and the performance of the algorithm depends on the searching process. Each EA features specific parameters, and a proper calibration helps to reduce the randomness factor and improves the effectiveness of the search for minima. More specifically, the only common parameter to all techniques is the initial size of the random population (P). It is well known that population size should be large enough to guarantee the diversity of solutions and must grow with the number of decision variables. However, the larger the population size, the slower the convergence process. This work attempts to determine the population size that yields better solutions in less time. In order to get that, the work applies a method based on the concept of efficiency (E) of an algorithm. This efficiency relates the quality of the obtained solution with the computational effort that every EA requires to find the final design solution. This ratio E also represents an objective indicator to compare the performance of different algorithms applied to WDN optimization. The proposed methodology is applied to the pipe-sizing problem of three medium-sized benchmark networks, such as Hanoi, New York Tunnel and GoYang networks. Thus, from the currently available algorithms, this work includes evolutionary methodologies based on a Pseudo-Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Harmony Search (HS). First, the different algorithm parameters for each network are calibrated. The values used for every EA are those that have been calculated in previous works. Secondly, specific parameters remain constant and the population size is modified. After more than 500,000 simulations, the influence of the population size is statistically analyzed in the final solutions. Finally, the efficiency was analyzed for each network and algorithm. The results ensure the best possible configuration based on the quality of the solutions and the convergence speed of the algorithm, depending of the population size.ElsevierDepartamento de Ingeniería Hidráulica y Medio AmbienteEscuela Técnica Superior de Ingeniería IndustrialRepositorio Institucional de la Universitat Politècnica de València Riunet20172017-01-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/108644reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/1086442026-06-13T07:49:27Z
dc.title.none.fl_str_mv Population size influence on the efficiency of evolutionary algorithms to design water networks
title Population size influence on the efficiency of evolutionary algorithms to design water networks
spellingShingle Population size influence on the efficiency of evolutionary algorithms to design water networks
Mora-Melia, Daniel
Water Distribution Systems
Design
Efficiency
Evolutionary Algorithms
MECANICA DE FLUIDOS
title_short Population size influence on the efficiency of evolutionary algorithms to design water networks
title_full Population size influence on the efficiency of evolutionary algorithms to design water networks
title_fullStr Population size influence on the efficiency of evolutionary algorithms to design water networks
title_full_unstemmed Population size influence on the efficiency of evolutionary algorithms to design water networks
title_sort Population size influence on the efficiency of evolutionary algorithms to design water networks
dc.creator.none.fl_str_mv Mora-Melia, Daniel
Gutiérrez-Bahamondes, Jimmy H.
Martínez-Solano, F. Javier|||0000-0002-8140-5960
Iglesias Rey, Pedro Luís|||0000-0001-8300-3255
author Mora-Melia, Daniel
author_facet Mora-Melia, Daniel
Gutiérrez-Bahamondes, Jimmy H.
Martínez-Solano, F. Javier|||0000-0002-8140-5960
Iglesias Rey, Pedro Luís|||0000-0001-8300-3255
author_role author
author2 Gutiérrez-Bahamondes, Jimmy H.
Martínez-Solano, F. Javier|||0000-0002-8140-5960
Iglesias Rey, Pedro Luís|||0000-0001-8300-3255
author2_role author
author
author
dc.contributor.none.fl_str_mv Departamento de Ingeniería Hidráulica y Medio Ambiente
Escuela Técnica Superior de Ingeniería Industrial
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Water Distribution Systems
Design
Efficiency
Evolutionary Algorithms
MECANICA DE FLUIDOS
topic Water Distribution Systems
Design
Efficiency
Evolutionary Algorithms
MECANICA DE FLUIDOS
description [EN] The optimal sizing in water distribution networks (WDN) is of great interest because it allows the selection of alternative economical solutions that ensure design requirements at nodes (demands and pressure) and at lines (velocities). Among all the available design methodologies, this work analyzes those based on evolutionary algorithms (EAs). EAs are a combination of deterministic and random approaches, and the performance of the algorithm depends on the searching process. Each EA features specific parameters, and a proper calibration helps to reduce the randomness factor and improves the effectiveness of the search for minima. More specifically, the only common parameter to all techniques is the initial size of the random population (P). It is well known that population size should be large enough to guarantee the diversity of solutions and must grow with the number of decision variables. However, the larger the population size, the slower the convergence process. This work attempts to determine the population size that yields better solutions in less time. In order to get that, the work applies a method based on the concept of efficiency (E) of an algorithm. This efficiency relates the quality of the obtained solution with the computational effort that every EA requires to find the final design solution. This ratio E also represents an objective indicator to compare the performance of different algorithms applied to WDN optimization. The proposed methodology is applied to the pipe-sizing problem of three medium-sized benchmark networks, such as Hanoi, New York Tunnel and GoYang networks. Thus, from the currently available algorithms, this work includes evolutionary methodologies based on a Pseudo-Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Harmony Search (HS). First, the different algorithm parameters for each network are calibrated. The values used for every EA are those that have been calculated in previous works. Secondly, specific parameters remain constant and the population size is modified. After more than 500,000 simulations, the influence of the population size is statistically analyzed in the final solutions. Finally, the efficiency was analyzed for each network and algorithm. The results ensure the best possible configuration based on the quality of the solutions and the convergence speed of the algorithm, depending of the population size.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/108644
url https://riunet.upv.es/handle/10251/108644
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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