Optimal learning group formation: A multi-objective heuristic search strategy for enhancing inter-group homogeneity and intra-group heterogeneity
作者：
Highlights：
• A heuristic search strategy was proposed for optimal learning group formation.
• NSGA-II, a multi-objective optimization tool, was utilized for optimal grouping.
• It was capable of enhancing inter-group homogeneity and Intra-group Heterogeneity.
• Efficient and reliable fitness functions were defined to stop iterations.
• Various characteristics of any data types and range of variations can be handled.
摘要
•A heuristic search strategy was proposed for optimal learning group formation.•NSGA-II, a multi-objective optimization tool, was utilized for optimal grouping.•It was capable of enhancing inter-group homogeneity and Intra-group Heterogeneity.•Efficient and reliable fitness functions were defined to stop iterations.•Various characteristics of any data types and range of variations can be handled.
论文关键词：Group formation,Multi-objective optimization,Collaborative learning,Inter-group homogeneity,Intra-group heterogeneity,Computational intelligence
论文评审过程：Received 10 March 2018, Revised 13 August 2018, Accepted 16 October 2018, Available online 17 October 2018, Version of Record 22 October 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.10.034
