A survey on examination Scheduling Problem (ESP) and hyper-heuristics approaches for solving ESP

Examination Scheduling is a divergent, combinatorial optimization problem which tends to be solved using stochastic search approaches such as evolutionary algorithms (EAs) and heuristic methods such as Hill-climbing, Simulated annealing, Tabu search, Genetic algorithms, Graph coloring etc. In this paper we discuss research on examination Scheduling Problem (ESP) and Hyper-Heuristics approaches used to solve Examination Scheduling. The last few years has seen an augmented level of attention on this important topic in academic organizations and universities. There have been significant contributions in theoretical and practical aspects. Different Algorithmic approaches to solve ESP are discussed. Classifications of Hyper-Heuristics approaches are discussed with different perspectives. These include Heuristics to choose heuristics and Heuristics to generate heuristics. These can be further categorized according to whether they are based on constructive or perturbative search. We discussed different HH approaches like Harmony Search-based Hyper-heuristic (HSHH), Hybrid variable neighborhood structure Hyper-Heuristics, applied Monte Carlo hyper-heuristics, Graph Coloring Constructive Hyper-Heuristic.