An improved particle swarm optimization with a new swap operator for team formation problem

Abstract Formation of effective teams of experts has played a crucial role in successful projects especially in social networks. In this paper, a new particle swarm optimization (PSO) algorithm is proposed for solving a team formation optimization problem by minimizing the communication cost among e...

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Main Authors: Walaa H. El-Ashmawi, Ahmed F. Ali, Mohamed A. Tawhid
Format: Article
Language:English
Published: Islamic Azad University 2018-07-01
Series:Journal of Industrial Engineering International
Subjects:
Online Access:http://link.springer.com/article/10.1007/s40092-018-0282-6
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spelling doaj-7cd10aba3035453889eb0e83c61693442021-03-02T11:12:52ZengIslamic Azad UniversityJournal of Industrial Engineering International1735-57022251-712X2018-07-01151537110.1007/s40092-018-0282-6An improved particle swarm optimization with a new swap operator for team formation problemWalaa H. El-Ashmawi0Ahmed F. Ali1Mohamed A. Tawhid2Department of Computer Science, Faculty of Computers and Informatics, Suez Canal UniversityDepartment of Computer Science, Faculty of Computers and Informatics, Suez Canal UniversityDepartment of Mathematics and Statistics, Faculty of Science, Thompson Rivers UniversityAbstract Formation of effective teams of experts has played a crucial role in successful projects especially in social networks. In this paper, a new particle swarm optimization (PSO) algorithm is proposed for solving a team formation optimization problem by minimizing the communication cost among experts. The proposed algorithm is called by improved particle optimization with new swap operator (IPSONSO). In IPSONSO, a new swap operator is applied within particle swarm optimization to ensure the consistency of the capabilities and the skills to perform the required project. Also, the proposed algorithm is investigated by applying it on ten different experiments with different numbers of experts and skills; then, IPSONSO is applied on DBLP dataset, which is an example for benchmark real-life database. Moreover, the proposed algorithm is compared with the standard PSO to verify its efficiency and the effectiveness and practicality of the proposed algorithm are shown in our results.http://link.springer.com/article/10.1007/s40092-018-0282-6Particle swarm optimizationTeam formation problemSocial networksSingle-point crossoverSwap operator
collection DOAJ
language English
format Article
sources DOAJ
author Walaa H. El-Ashmawi
Ahmed F. Ali
Mohamed A. Tawhid
spellingShingle Walaa H. El-Ashmawi
Ahmed F. Ali
Mohamed A. Tawhid
An improved particle swarm optimization with a new swap operator for team formation problem
Journal of Industrial Engineering International
Particle swarm optimization
Team formation problem
Social networks
Single-point crossover
Swap operator
author_facet Walaa H. El-Ashmawi
Ahmed F. Ali
Mohamed A. Tawhid
author_sort Walaa H. El-Ashmawi
title An improved particle swarm optimization with a new swap operator for team formation problem
title_short An improved particle swarm optimization with a new swap operator for team formation problem
title_full An improved particle swarm optimization with a new swap operator for team formation problem
title_fullStr An improved particle swarm optimization with a new swap operator for team formation problem
title_full_unstemmed An improved particle swarm optimization with a new swap operator for team formation problem
title_sort improved particle swarm optimization with a new swap operator for team formation problem
publisher Islamic Azad University
series Journal of Industrial Engineering International
issn 1735-5702
2251-712X
publishDate 2018-07-01
description Abstract Formation of effective teams of experts has played a crucial role in successful projects especially in social networks. In this paper, a new particle swarm optimization (PSO) algorithm is proposed for solving a team formation optimization problem by minimizing the communication cost among experts. The proposed algorithm is called by improved particle optimization with new swap operator (IPSONSO). In IPSONSO, a new swap operator is applied within particle swarm optimization to ensure the consistency of the capabilities and the skills to perform the required project. Also, the proposed algorithm is investigated by applying it on ten different experiments with different numbers of experts and skills; then, IPSONSO is applied on DBLP dataset, which is an example for benchmark real-life database. Moreover, the proposed algorithm is compared with the standard PSO to verify its efficiency and the effectiveness and practicality of the proposed algorithm are shown in our results.
topic Particle swarm optimization
Team formation problem
Social networks
Single-point crossover
Swap operator
url http://link.springer.com/article/10.1007/s40092-018-0282-6
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