Metaheuristics for University Course Timetabling

Abstract

The work presented in this thesis concerns the problem of timetabling at universitiesparticularly course-timetabling, and examines the various ways in which metaheuristic techniques might be applied to these sorts of problems. Using a popular benchmark version of a university course timetabling problem, we examine the implications of using a "twostaged" algorithmic approach, whereby in stage-one only the mandatory constraints are considered for satisfaction, with stage-two then being concerned with satisfying the remaining constraints but without re-breaking any of the mandatory constraints in the process.Consequently, algorithms for each stage of this approach are proposed and analysed in detail.For the first stage we examine the applicability of the so-called Grouping Genetic Algorithm (GGA). In our analysis of this algorithm we discover a number of scaling-up issues surrounding the general GGA approach and discuss various reasons as to why this is so. Two separate ways of enhancing general performance are also explored. Secondly, an Iterated Heuristic Search algorithm is also proposed for the same problem, and in experiments it is shown to outperform the GGA in almost all cases. Similar observations to these are also witnessed in a second set of experiments, where the analogous problem of colouring equipartite graphs is also considered.Two new metaheuristic algorithms are also proposed for the second stage of the twostaged approach: an evolutionary algorithm (with a number of new specialised evolutionary operators), and a simulated annealing-based approach. Detailed analyses of both algorithms are presented and reasons for their relative benefits and drawbacks are discussed.Finally, suggestions are also made as to how our best performing algorithms might be modified in order to deal with further "real-world" constraints. In our analyses of these modified algorithms, as well as witnessing promising behaviour in some cases, we are also able to highlight some of the limitations of the two-stage approach in certain cases.ii Table of Fig. 3.2:A demonstration of the matrix representation for timetables used throughout this thesis. Here, event 11 has been assigned to room 2 and timeslot 2, event 8 has been assigned to room 2, timeslot 11, and so on. Also indicated in this diagram is the presence of the end-of-day timeslots (which will occur in timeslots 9, 18, 27, 36 and 45). These might be considered slightly different to the remaining forty timeslots, because events that are assigned to these will automatically cause soft constraint SC to have a higher distance-to-feasibility than the best candidate solution in the initial population of the GGA, and will thus generally start at a higher point on the y-axis. 84 1: IntroductionTimetables are ubiquitous in many areas of daily life such as work, education, transport, and entertainment. Indeed, it is quite difficult to imagine an organized and modern society coping without them. Yet in many real-world cases, particularly where resources (such as peopl...

Setting the Research Agenda in Automated Timetabling: The Second International Timetabling Competition

“…An overview of the techniques submited is given in the following (Abdullah et al(2007), Lewis et al (2007)). The following sections highlights the main areas of difference between the two competitions.…”

“…Details on applied techniques and results can be found at the webpage http://www.idsia.ch/Files/ttcomp2002/. More recently, this formulation has become somewhat of a standard within the research area with many researchers using it and the associated generated datasets within their work [Abdullah et al (2007), Chiarandini et al (2006), Di Gaspero and Schaerf (2006), Kostuch (2005), Lewis et al (2007b)]. ITC2002 has therefore been successful in generating common ground for cross-fertilisation of ideas for research groups within the timetabling community.…”

“…Technical reports (McCollum et al (2007b), Lewis et al (2007), Di ) are available on the competition web site for each track detailing all aspects of the formulation offered. In this work, following a description of the main aspects of the competition, an overview of each track is provided along with results on the datasets released as part of the competition.…”

On the application of graph colouring techniques in round-robin sports scheduling

“…In this paper our intention is to follow this approach, though we also choose to view sports timetabling as a type of graph colouring problem, enabling us to borrow various techniques from the graph-colouring literature. We note that graph colouring concepts are often used with other types of scheduling problem, particularly university timetabling problems [43,8,28], though this has not previously been the case with sports scheduling. In Section 2 we thus begin by describing how basic RR problems can be represented as graph colouring problems, and discuss the properties of such graphs.…”

Using Color Coded Pattern Clustering Model Combined with Automated System for Courses Scheduling

“…[4] specified that "The problem of constructing course timetables for academic institutions consists of allocating the set of courses offered by the university to time periods and classrooms in such a way that no teacher, student or room is used more than once per period and that room capacities are not exceeded". Students and instructors cannot be at two different places at the same time which is called event-clash constraint by [5]. Event-clash is considered to be a hard constraint that cannot be violated because the solution will become not feasible [ 6,7].…”