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Abstract. This paper describes the results of a questionnaire on examination thnetabling sent to the registrars of ninety five British Universities. The survey asked questions in three specific categories. Firstly, universities were asked about the nature of their examination timetabling problem: how many people, rooms, periods are involved and what difficulties are associated with the problem? Secondly, we asked about how the problem is solved at theh' institution and whether a manual or automated system is used. Lastly, we asked what qualities are required in a good timetable. We conclude by making some comments, based on the sm'vey replies, as to what sort of criteria a general automated timetabling system must meet.

This document seeks to provide a scientific basis by which different initialization algorithms for evolutionary timetabling may be compared. Seeding the initial population may be used to improve initial quality and provide a better starting point for the evolutionary algorithm. This must be tempered against the consideration that if the seeding algorithm produces very similar solutions, then the loss of genetic diversity may well lead to a worse final solution. Diversity, we hope, provides a good indication of how good the final solution will be, although only by running the evolutionary algorithm will the exact result be found. We will investigate the effects of heuristic seeding by taking quality and diversity measures of populations generated by heuristic initialization methods on both random and real-life data, as well as assessing the long-term performance of an evolutionary algorithm (found to work well on the timetabling problem) when using heuristic initialization. This will show how the use of heuristic initialization strategies can substantially improve the performance of evolutionary algorithms for the timetabling problem.

The problem of constructing an automated system for use with timetabling is particularly well known. Many programs exist for this task, but they peiform well only in particular, isolated environments. Currently being developed is a general system that will be able to cope with the ever-changing requirements of large educational institutions. This article presents a description of the methods and techniques behind such a system. Graph colouring and room allocation algorithms are presented, and ways of combining the two to provide a basis for a flexible and widely applicable timetabling system are shown. This article also describes how several common timetabling features can be handled within the system. The problems of intractability are overcome by producing a spreadsheet-type system that the user can guide in an informed and useful way. This gives the user control of the search and offers the possibility of backtracking where no reasonable solution is found, while still letting the heuristic algorithms do the hard work. Such an approach cannot guarantee an optimal solution, but it can guarantee a solution with which the user is happy. It is assumed that any user addressing a timetabling problem in a university environment has some idea of the timetable required and is qualified to judge whether a solution is suitable. (

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