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Solving the student grouping problem in e‐learning systems using swarm intelligence metaheuristics
Author(s) -
Alhunitah Hamad,
Menai Mohamed El Bachir
Publication year - 2016
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.21752
Subject(s) - metaheuristic , swarm intelligence , particle swarm optimization , ant colony optimization algorithms , computer science , parallel metaheuristic , ant colony , artificial intelligence , computational intelligence , swarm behaviour , mathematical optimization , machine learning , mathematics , meta optimization
The student grouping problem (SGP) is NP‐hard; however, obtaining approximate solutions is essential to collaborative work in e‐learning. This paper explores swarm intelligence metaheuristics including particle swarm optimization (PSO), ant colony system (ACS), and artificial bee colony (ABC) to solve the student grouping problem and create heterogeneous groups. © 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ 24:831–842, 2016; View this article online at wileyonlinelibrary.com/journal/cae ; DOI 10.1002/cae.21752