A variable neighborhood search for creating student groups with similar characteristics

Abstract

This paper considers real problem of assigning students from Belgrade Business School to study groups in such a way that each group provides a good representation of the classroom population. We consider this problem as a general Balanced Multi-Weighted Attribute Set Partitioning (BMWASP) problem which requires finding a partition of a given set of objects with multiple weighted attributes into a certain number of groups so that each attribute is evenly distributed amongst the groups. To solve instances from Belgrade Business School, we have developed a heuristic method based on a Variable Neighborhood Search (VNS). A local search procedure with efficient fast swap-based local search is implemented in the proposed VNS-based approach.