An improved particle swarm optimization with a new swap operator for team formation problem
محورهای موضوعی : Mathematical Optimization
Walaa H. El-Ashmawi
1
(Department of Computer Science, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt)
Ahmed F . Ali
2
(Department of Computer Science, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt)
Mohamed A. Tawhid
3
(Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, Kamloops, BC, V2C 0C8, Canada)
کلید واژه: Particle swarm optimization . Team formation problem . Social networks . Single, point crossover . Swap operator,
چکیده مقاله :
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.
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