This randomized trial demonstrates the optimization of online class schedules using advanced scheduling algorithms, suggesting improved efficiency in lesson timetabling.
The paper addresses university lesson timetabling with a focus on online education, reviews key algorithmic approaches, and proposes a structured set of criteria for the dispatching task. Algorithms covered include graph coloring, constraint-based methods, genetic algorithms, simulated annealing, tabu search, integer linear programming, and various heuristic and hybrid techniques. The dispatching criteria are split into two tiers: basic constraints shared with offline scheduling (curriculum sizing and lecturer time slots) and online-specific criteria (discipline weight factor, time slot priorities, knowledge control form, lesson sequencing, and load balancing). A hybrid resolution approach combining constraint programming, integer linear programming, and meta-heuristic methods is proposed as the most effective strategy for handling the defined constraint set.
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Sytnik et al. (2024) studied this question.
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