Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem

[EN] Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WA...

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Autor: Al-Khazraji, Huthaifa
Tipo de recurso: artículo
Fecha de publicación:2022
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:10251/180597
Acceso en línea:https://riunet.upv.es/handle/10251/180597
Access Level:acceso abierto
Palabra clave:Servitization
Resource Assignment Problem
Workers Assignment Problem
Metaheuristic Optimization
Whale Optimization Algorithm
Flower Pollination Algorithm
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spelling Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problemAl-Khazraji, HuthaifaServitizationResource Assignment ProblemWorkers Assignment ProblemMetaheuristic OptimizationWhale Optimization AlgorithmFlower Pollination Algorithm[EN] Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WAP is an NP-hard combinatorial optimization problem. Due to its importance, several algorithms have been developed to solve it. In this paper, it is considered that a manager is required to provide a training course to his workers in order to improve their level of skill or experience to have a sustainable competitive advantage in the industry. The training cost of each worker to perform a particular job is different. The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. MATLAB Software is used to perform the simulation of the two proposed methods into WAP. The computational results for a set of randomly generated problems of various sizes show that the FPA is able to find good quality solutions.Universitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20222022-01-31journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/180597reponame: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:10251/1805972026-06-13T07:49:27Z
dc.title.none.fl_str_mv Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
title Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
spellingShingle Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
Al-Khazraji, Huthaifa
Servitization
Resource Assignment Problem
Workers Assignment Problem
Metaheuristic Optimization
Whale Optimization Algorithm
Flower Pollination Algorithm
title_short Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
title_full Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
title_fullStr Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
title_full_unstemmed Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
title_sort Comparative study of whale optimization algorithm and flower pollination algorithm to solve workers assignment problem
dc.creator.none.fl_str_mv Al-Khazraji, Huthaifa
author Al-Khazraji, Huthaifa
author_facet Al-Khazraji, Huthaifa
author_role author
dc.contributor.none.fl_str_mv Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Servitization
Resource Assignment Problem
Workers Assignment Problem
Metaheuristic Optimization
Whale Optimization Algorithm
Flower Pollination Algorithm
topic Servitization
Resource Assignment Problem
Workers Assignment Problem
Metaheuristic Optimization
Whale Optimization Algorithm
Flower Pollination Algorithm
description [EN] Many important problems in engineering management can be formulated as Resource Assignment Problem (RAP). The Workers Assignment Problem (WAP) is considered as a sub-class of RAP which aims to find an optimal assignment of workers to a number of tasks in order to optimize certain objectives. WAP is an NP-hard combinatorial optimization problem. Due to its importance, several algorithms have been developed to solve it. In this paper, it is considered that a manager is required to provide a training course to his workers in order to improve their level of skill or experience to have a sustainable competitive advantage in the industry. The training cost of each worker to perform a particular job is different. The WAP is to find the best assignment of workers to training courses such that the total training cost is minimized. Two metaheuristic optimizations named Whale Optimization Algorithm (WOA) and Flower Pollination Algorithm (FPA) are utilized to final the optimal solution that reduces the total cost. MATLAB Software is used to perform the simulation of the two proposed methods into WAP. The computational results for a set of randomly generated problems of various sizes show that the FPA is able to find good quality solutions.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-31
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/10251/180597
url https://riunet.upv.es/handle/10251/180597
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 Universitat Politècnica de València
publisher.none.fl_str_mv Universitat Politècnica de València
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
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