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Examination Timetabling with Independent Resource Pools: A Multi-Stage Genetic Algorithm Approach

Khalil Chebil¹   , Mahdi Khemakhem¹   , Abdallah Hammad¹   , Mohammed Alanazi¹   

1. Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al Kharj 11942, Saudi Arabia
   k.chebil@psau.edu.sa (corresponding author), m.khemakhem@psau.edu.sa, 442052035@std.psau.edu.sa, 442052038@std.psau.edu.sa

Abstract

The Examination Timetabling Problem (ETP) is an NP-hard combina torial optimization problem that has been extensively studied over the past decades, with methodologies ranging from classical heuristics to contemporary machine learn ing approaches. This paper provides a comprehensive literature review and proposes a novel two-stage genetic algorithm based decomposition combined with a clear lin ear mathematical formulation. A unique contribution of this work is addressing the practical complexity of two-separated examination facilities at PSAU, where male and female students study in completely separate buildings with independent ex amination rooms, capacities, and supervisory staff, yet must follow a synchronized examination schedule. This creates a coupled dual-ETP problem where two inde pendent resource allocation problems must share identical time slot assignments, significantly increasing model complexity and constraint interactions. The proposed algorithm decomposes the problem into two sequential stages,time slot assignment and room assignment to effectively reduce computational complexity while main taining solution quality. Additionally, a systematic comparison with Mixed-Integer Programming (MIP) formulation is provided to establish the trade-offs between ex act and metaheuristic approaches. The algorithm is further benchmarked against simulated annealing and tabu search baselines to provide broader methodological context, demonstrating its advantage on coupled dual-resource instances. The algo rithm shows particular strength in scalability, successfully solving large instances where MIP becomes computationally intractable, while maintaining competitive so lution quality.

Key words

Examination, Timetabling, Genetic Algorithm, Optimization.

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS251220025C

Publication information

Volume 23, Issue 3 (June 2026)
Year of Publication: 2026
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Chebil, K., Khemakhem, M., Hammad, A., Alanazi, M.: Examination Timetabling with Independent Resource Pools: A Multi-Stage Genetic Algorithm Approach. Computer Science and Information Systems, 23(3), 1027–1052 (2026). https://doi.org/10.2298/CSIS251220025C