Examination Timetabling in British Universities: A Survey
Selected papers from the First International Conference on Practice and Theory of Automated Timetabling
Case-based heuristic selection for timetabling problems
Journal of Scheduling
An informed genetic algorithm for the examination timetabling problem
Applied Soft Computing
Examination timetabling using late acceptance hyper-heuristics
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A study into the use of hyper-heuristics to solve the school timetabling problem
SAICSIT '10 Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
A graph coloring constructive hyper-heuristic for examination timetabling problems
Applied Intelligence
Population based Local Search for university course timetabling problems
Applied Intelligence
An evolutionary-based hyper-heuristic approach for the Jawbreaker puzzle
Applied Intelligence
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This paper presents an iterative adaptive approach which hybridises bin packing heuristics to assign exams to time slots and rooms. The approach combines a graph-colouring heuristic, to select an exam in every iteration, with bin-packing heuristics to automate the process of time slot and room allocation for exam timetabling problems. We start by analysing the quality of the solutions obtained by using one heuristic at a time. Depending on the individual performance of each heuristic, a random iterative hyper-heuristic is used to randomly hybridise the heuristics and produce a collection of heuristic sequences to construct solutions with different quality. Based on these sequences, we analyse the way in which the bin packing heuristics are automatically hybridised. It is observed that the performance of the heuristics used varies depending on the problem. Based on these observations, an iterative hybrid approach is developed to adaptively choose and hybridise the heuristics during solution construction. The overall aim here is to automate the heuristic design process, which draws upon an emerging research theme which is concerned with developing methods to design and adapt heuristics automatically. The approach is tested on the exam timetabling track of the second International Timetabling Competition, to evaluate its ability to generalise on instances with different features. The hyper-heuristic with low-level graph-colouring and bin-packing heuristics approach was found to generalise well over all the problem instances and performed comparably to the state of the art approaches.