Heuristic approaches for real world examination timetabling problems

The examination timetabling (exam-timeslot-room assignment) problem involves assigning exams to a specific or limited number of timeslots and rooms, with the aim of satisfying the hard constraints and the soft constraints as much as possible. Most of the techniques reported in the literature have been applied to solve simplified examination benchmark datasets, available within the scientific literature. In this research we bridge the gap between research and practice by investigating a problem taken from the Universiti Malaysia Pahang (UMP), a real world capacitated examination timetabling problem. This dataset has several novel constraints, in addition to those commonly used in the literature. Additionally, the invigilator scheduling problem (invigilator assignment) was also investigated as it has not received the same level of research attention as the examination scheduling (although it is just as important to educational institutions). The formal models are defined, and constructive heuristics was developed for both problems in which the overall problems are solved with a two-phase approach which involves scheduling the exam to timeslot and room, and follows with scheduling the invigilator. During the invigilator assignment, we assume that there is already an examination timetable in place (i.e. previously generated). It reveals that the invigilator scheduling solution dependent on the number of rooms selected from the exam-timeslot-room assignment phase (i.e. a lesser number of used rooms would minimises the invigilation duties for staff), this encourages us to further improve the exam-timeslot-room timetable solution. An improvement on the result was carried out using modified extended great deluge algorithm (modified-GDA) and multi-neighbourhood GDA approach (that use more than one neighbourhood during the search). The modified-GDA uses a simple to understand parameter and allows the boundary that acts as the acceptance level, to dynamically change during the search. The propose approaches able to produce good quality solution when compared to the solutions from the proprietary software used by UMP. In addition, our solutions adhere to all hard constraints which the current systems fail to do. Finally, we extend our research onto investigating the Second International Timetabling Competition (ITC2007) dataset as it also contains numerous constraints much similar to UMP datasets. Our propose approach able to produce competitive solutions when compared to the solutions produced by other reported works in the literature

Heuristic approaches for real world examination timetabling problems

The examination timetabling (exam-timeslot-room assignment) problem involves assigning exams to a specific or limited number of timeslots and rooms, with the aim of satisfying the hard constraints and the soft constraints as much as possible. Most of the techniques reported in the literature have been applied to solve simplified examination benchmark datasets, available within the scientific literature. In this research we bridge the gap between research and practice by investigating a problem taken from the Universiti Malaysia Pahang (UMP), a real world capacitated examination timetabling problem. This dataset has several novel constraints, in addition to those commonly used in the literature. Additionally, the invigilator scheduling problem (invigilator assignment) was also investigated as it has not received the same level of research attention as the examination scheduling (although it is just as important to educational institutions). The formal models are defined, and constructive heuristics was developed for both problems in which the overall problems are solved with a two-phase approach which involves scheduling the exam to timeslot and room, and follows with scheduling the invigilator. During the invigilator assignment, we assume that there is already an examination timetable in place (i.e. previously generated). It reveals that the invigilator scheduling solution dependent on the number of rooms selected from the exam-timeslot-room assignment phase (i.e. a lesser number of used rooms would minimises the invigilation duties for staff), this encourages us to further improve the exam-timeslot-room timetable solution. An improvement on the result was carried out using modified extended great deluge algorithm (modified-GDA) and multi-neighbourhood GDA approach (that use more than one neighbourhood during the search). The modified-GDA uses a simple to understand parameter and allows the boundary that acts as the acceptance level, to dynamically change during the search. The propose approaches able to produce good quality solution when compared to the solutions from the proprietary software used by UMP. In addition, our solutions adhere to all hard constraints which the current systems fail to do. Finally, we extend our research onto investigating the Second International Timetabling Competition (ITC2007) dataset as it also contains numerous constraints much similar to UMP datasets. Our propose approach able to produce competitive solutions when compared to the solutions produced by other reported works in the literature

Models, solution methods and threshold behaviour for the teaching space allocation problem

Universities have to manage their teaching space, and plan future needs. Their efforts are frequently hampered by, capital and maintenance costs, on one hand, pedagogical and teaching services on the other. The efficiency of space usage, can be measured by the utilisation: the percentage of available seat-hours actually used. The observed utilisation, in many institutions, is unacceptably low, and this provides our main underlying motivation: To address and assess some of the major factors that affect teaching space usage in the hope of improving it in practise. Also, when performing space management, managers operate within a limited number and capacity of lecture theatres, tutorial rooms, etc. Hence, some teaching activities require splitting into different groups. For example, lectures being too large to fit in any one room and seminars/tutorials being taught in small groups for good teaching practise. This thesis forms the cornerstone of ongoing research to illuminate issues stemming from poorly utilised space and studies the nature of constraints that underlies those low levels of utilisation. We give quantitative evidence that constraints related to timetabling are major players in pushing down utilisation levels and also, devise "Dynamic Splitting" algorithms to illustrate the effects of splitting on utilisation levels. We showed the existence of threshold between phases where splitting and allocation is "always possible" to ones where "it's never possible", hence, introducing a practical application of Phase Transition to space planning and management. We have also worked on the long-term planning aspect of teaching space and proposed methods to improve the future expected utilisation

Train planning in a fragmented railway: a British perspective

Train Planning (also known as railway scheduling) is an area of substantial importance to the success of any railway. Through train planning, railway managers aim to meet the needs of customers whilst using as low a level of resources (infrastructure, rolling stock and staff) as possible. Efficient and effective train planning is essential to get the best possible performance out of a railway network. The author of this thesis aims, firstly, to analyse the processes which are used to develop train plans and the extent to which they meet the objectives that they might be expected to meet and, secondly, to investigate selected new and innovative software approaches that might make a material difference to the effectiveness and/or efficiency of train planning processes. These aims are delivered using a range of primarily qualitative research methods, including literature reviews, interviews, participant observation and case studies, to understand these processes and software. Conclusions regarding train planning processes include how the complexity of these processes hinders their effectiveness, the negative impact of the privatisation of British Rail on these processes and the conflicting nature of objectives for train planning in the privatised railway. Train planning software is found not to adequately support train planners in meeting the objectives they are set. The potential for timetable generation using heuristics and for timetable performance simulation to improve the effectiveness of train planning are discussed and recommendations made for further research and development to address the limitations of the software currently available

A genetic programming hyper-heuristic approach to automated packing

This thesis presents a programme of research which investigated a genetic programming hyper-heuristic methodology to automate the heuristic design process for one, two and three dimensional packing problems. Traditionally, heuristic search methodologies operate on a space of potential solutions to a problem. In contrast, a hyper-heuristic is a heuristic which searches a space of heuristics, rather than a solution space directly. The majority of hyper-heuristic research papers, so far, have involved selecting a heuristic, or sequence of heuristics, from a set pre-defined by the practitioner. Less well studied are hyper-heuristics which can create new heuristics, from a set of potential components. This thesis presents a genetic programming hyper-heuristic which makes it possible to automatically generate heuristics for a wide variety of packing problems. The genetic programming algorithm creates heuristics by intelligently combining components. The evolved heuristics are shown to be highly competitive with human created heuristics. The methodology is first applied to one dimensional bin packing, where the evolved heuristics are analysed to determine their quality, specialisation, robustness, and scalability. Importantly, it is shown that these heuristics are able to be reused on unseen problems. The methodology is then applied to the two dimensional packing problem to determine if automatic heuristic generation is possible for this domain. The three dimensional bin packing and knapsack problems are then addressed. It is shown that the genetic programming hyper-heuristic methodology can evolve human competitive heuristics, for the one, two, and three dimensional cases of both of these problems. No change of parameters or code is required between runs. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains

Fuzzy methodologies for automated University timetabling solution construction and evaluation

This thesis presents an investigation into the use of fuzzy methodologies for University timetabling problems. The first area of investigation is the use of fuzzy techniques to combine multiple heuristic orderings within the construction of timetables. Different combinations of multiple heuristic ordering were examined, considering five graph-based heuristic orderings - Largest Degree, Saturation Degree, Largest Enrolment, Largest Coloured Degree and Weighted Largest Degree. The initial development utilised only two heuristic orderings simultaneously and subsequent development went on to incorporate three heuristic orderings simultaneously. A central hypothesis of this thesis is that this approach provides a more realistic scheme for measuring the difficulty of assigning events to time slots than the use of a single heuristic alone. Experimental results demonstrated that the fuzzy multiple heuristic orderings (with parameter tuning) outperformed all of the single heuristic orderings and non-fuzzy linear weighting factors. Comprehensive analysis has provided some key insights regarding the implementation of multiple heuristic orderings. Producing examination timetables automatically has been the subject of much research. It is generally the case that a number of alternative solutions that satisfy all the hard criteria are possible. Indeed, there are usually a very large number of such feasible solutions. Some method is required to permit the overall quality of different solutions to be quantified, in order to allow them to be compared, so that the best may be selected. In response to that demand, the second area of investigation of this thesis is concerned with a new evaluation function for examination timetabling problems. A novel approach, in which fuzzy methods are used to evaluate the end solution quality, separate from the objective functions used in solution generation, represents a significant addition to the literature. The proposed fuzzy evaluation function provides a mechanism to allow an overall decision in evaluating the quality of a timetable solution to be made based on common sense rules that encapsulate the notion that the timetable solution quality increases as both the average penalty and the highest penalty decrease. New algorithms to calculate what is loosely termed the lower limits and upper limits of the proximity cost function for any problem instance are also presented. These limits may be used to provide a good indication of how good any timetable solution is. Furthermore, there may be an association between the proposed lower limit and the formal lower bound. This is the first time that lower limits (other than zero) have been established for proximity cost evaluation of timetable solutions

Hochflexibles Workforce Management

It can be observed that companies tend to use a very demand driven personnel scheduling instead of using fixed shifts. In this context the term highly flexible workforce management (WFM) is used. With instruments such as the planning of subdaily workplace rotations, the combination of working time model generation and personnel scheduling or the combination of personnel scheduling and vehicle routing the demand for personnel can be covered very well. Such problems are novel and found little attention by researchers up to now.In this work classical OR-algorithms, metaheuristics and multi-agent systems (MAS) are evaluated on real world problems from logistics, retail and British Telecom. It can be shown, that classical OR-algorithms are not appropriate for these problems of highly flexible WFM, because of impractical CPU-times. On the other hand selected metaheuristics are very suitable. MAS should not be favoured, because selected metaheuristics performed always better. It must point out that a hybrid algorithm (a metaheuristic with a problem-specific repair) is responsible for the success of metaheuristics. MAS lack of a central planning instance that makes major changes for which agents are not able to do. Numerous algorithms of this work where originally developed for continuous problems. The adaption to combinatorial problems is described too. The appropriate adaption of parameters is also addressed.Zunehmend ist bei Unternehmen ein Trend weg von der starren Schicht- oder Dienstplanung hin zu einer auf den Personalbedarf ausgerichteten Planung festzustellen. In diesem Zusammenhang wird der Begriff hochflexibles Workforce Management (WFM) geprägt. Mit Instrumenten wie der Planung untertägiger Arbeitsplatzwechsel, der Kombination aus Arbeitszeitmodellerstellung und Einsatzplanung sowie der kombinierten Personaleinsatz- und Tourenplanung kann der Personaleinsatz sehr gut an den Personalbedarf angepasst werden. Derartige Problemstellungen sind neuartig und fanden in der Forschung bisher wenig Beachtung

Aplicación de la Teoría de Juegos a la programación de vuelos

Estudiamos en este trabajo una situación de tres compañías aéreas que vuelan a cinco ciudades desde un aeropuerto ficticio. Todas las compañías son análogas en costes y beneficios pero saturan la capacidad del aeropuerto. Creamos un grafo de colores, un color por cada compañía aérea, que une las distintas ciudades a donde vuelen. Creamos a su vez un valor basado en Myerson y en los grafos de colores para medir la importancia de cada compañía en función de la posición de las ciudades a donde vuelan en el grafo de colores. En nuestro caso no hay resultados muy sorpresivos ya que eliminamos una compañía que vuela a 3 ciudades y parece que esto debe pasar ante la que vuela a 4 aunque esto no es verdad en general debido a que el valor depende de la posición de las ciudades en el grafo de colores.We study in this work a situation of three airlines that fly to five cities from a fictitious airport. All companies are analogous in costs and benefits but they saturate the capacity of the airport. We create a graph of colors, a color for each airline, which links the different cities where they fly. We also create a value based on Myerson and the color graphs to measure the importance of each company based on the position of the cities where they fly in the color graph. In our case there are no very surprising results since we eliminate a company that flies to 3 cities and it seems that this should happen before the one that flies to 4 although this is not true in general because the value depends on the position of the cities in the color graph.Universidad de Sevilla. Grado en Ingeniería de las Tecnologías Industriale