Meta-heuristic approaches for the University Course Timetabling Problem

Course timetabling is an ongoing challenge that universities face all around the world. This combinatorial optimization task involves allocating a set of events into finite time slots and rooms while attempting to satisfy a set of predefined constraints. Given the high number of constraints and the large solution space to be explored, the University Course Timetabling Problem (UCTP) is classified as an NP-hard problem. Meta-heuristic approaches have been commonly applied to this problem in the literature and have achieved high performance on benchmark datasets. This survey paper provides a comprehensive and systematic review of these approaches in the UCTP. It reviews, summarizes, and categorizes the approaches, and introduces a classification for hybrid meta-heuristic methods. Furthermore, it critically analyzes the benefits and limitations of the methods. It also presents challenges, gaps, and possible future work. •A comprehensive overview of the UCTP, its variants, and benchmark datasets are given.•Recent (hybrid) meta-heuristics for the UCTP are analyzed and categorized.•Hybrid meta-heuristics are categorized into collaborative and integrative.•Hybrid meta-heuristics appear to be an emerging trend in recent years (2015 onwards).•Strengths and limitations of different approaches and future directions are discussed.