Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/267616 
Erscheinungsjahr: 
2019
Quellenangabe: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Volume:] 15 [Issue:] 1 [Publisher:] Springer [Place:] Heidelberg [Year:] 2019 [Pages:] 53-71
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
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.
Schlagwörter: 
Particle swarm optimization
Team formation problem
Social networks
Single-point crossover
Swap operator
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article

Datei(en):
Datei
Größe





Publikationen in EconStor sind urheberrechtlich geschützt.