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Although there has been a fair amount of research in the area of school timetabling, this domain has not developed as well as other fields of educational timetabling such as university course and examination timetabling. This can possibly be attributed to the fact that the studies in this domain have generally been conducted in isolation of each other and(More)
Earlier research into the examination timetabling problem focused on applying different methodologies to generate solutions to the problem. More recently research has been directed at developing hyper-heuristic systems for timetable construction. Hyper-heuristic systems are used to decide which examination to schedule next during the timetable construction(More)
Hyper-heuristics are aimed at providing a generalized solution to optimization problems rather than producing the best result for one or more problem instances. This paper examines the use of evolutionary algorithm (EA) selection hyper-heuristics to solve the offline one-dimensional bin-packing problem. Two EA hyper-heuristics are evaluated. The first(More)
This paper reports on the results of a preliminary study conducted to evaluate genetic programming (GP) as a means of evolving finite state transducers. A genetic programming system representing each individual as a directed graph was implemented to evolve Mealy machines. Tournament selection was used to choose parents for the next generation and the(More)
Research in the domain of examination timetabling is moving towards developing methods that gener-alise well over a range of problems. This is achieved by implementing hyper-heuristic systems to find the best heuristic or heuristic combination to allocate examinations when constructing a timetable for a problem. Heuristic combinations usually take the form(More)
Research in the field of examination timetabling has developed in two directions. The first looks at applying various methodologies to induce examination timetables. The second takes an indirect approach to the problem and examines the generation of heuristics or combinations of heuristics, i.e. hyper-heuristics, to be used in the construction of(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: The induction of examination timetables is a well researched field and various(More)
This paper presents a genetic programming (GP) hyper-heuristic approach that optimizes a search space of functions to assess the difficulty of allocating an examination during the timetable construction process. Each function is a heuristic combination of low-level construction heuristics combined by logical operators. The approach is tested on a set of(More)