Design and implementation of an android and web-based university timetable customization system

Timetabling is an essential component of scheduling in all sectors of education. University timetabling entails the scheduling of times and venues for lectures and examinations. These activities are logically structured in a time-wise manner and presented on papers and placed on notice boards in order to avoid conflicts of event. However, timetable schedule forgetfulness, misinterpretation, miscopying, cost of rescheduling and slow time to reach for the rescheduled timetables are the challenges posed by the use of paper and notice board-based timetables; hence, the need for automated timetables. In this paper, we discuss the implementation of Android and web-based timetable customization systems for the Faculty of Computer Science and Information Technology, Bayero University, Kano-Nigeria. The web-based system provides an administrative module that facilitates scheduling and rescheduling of lecture, examination and invigilation timetables. In addition, the Android timetable customization system permits the user to view, customize, set reminders and provide rescheduled timetable updates.Keywords: Android, Customization, Timetable and Web base

MetroNG: Computer-Aided Scheduling and Collision Detection

In this paper, we propose a formal model of the objects involved in a class of scheduling problems, namely in the classroom scheduling in universities which allow a certain degree of liberty in their curricula. Using the formal model, we present efficient algorithms for the detection of collisions of the involved objects and for the inference of a tree-like navigational structure in an interactive scheduling software allowing a selection of the most descriptive view of the scheduling objects. These algorithms were used in a real-world application called MetroNG; a visual interactive tool that is based on more than 10 years of experience we have in the field. It is currently used by the largest universities and colleges in the Czech Republic. The efficiency and usability of MetroNG suggests that our approach may be applied in many areas where multi-dimensionally structured data are presented in an interactive application

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions

Modifying Regeneration Mutation and Hybridising Clonal Selection for Evolutionary Algorithms Based Timetabling Tool

This paper outlines the development of a new evolutionary algorithms based timetabling (EAT) tool for solving course scheduling problems that include a genetic algorithm (GA) and a memetic algorithm (MA). Reproduction processes may generate infeasible solutions. Previous research has used repair processes that have been applied after a population of chromosomes has been generated. This research developed a new approach which (i) modified the genetic operators to prevent the creation of infeasible solutions before chromosomes were added to the population; (ii) included the clonal selection algorithm (CSA); and the elitist strategy (ES) to improve the quality of the solutions produced. This approach was adopted by both the GA and MA within the EAT. The MA was further modified to include hill climbing local search. The EAT program was tested using 14 benchmark timetabling problems from the literature using a sequential experimental design, which included a fractional factorial screening experiment. Experiments were conducted to (i) test the performance of the proposed modified algorithms; (ii) identify which factors and interactions were statistically significant; (iii) identify appropriate parameters for the GA and MA; and (iv) compare the performance of the various hybrid algorithms. The genetic algorithm with modified genetic operators produced an average improvement of over 50%

Problema de atribuição de vigilâncias de exames a docentes

O presente trabalho foi realizado com o intuito de resolver o problema de alocação de vigilantes a exames do Instituto Superior de Engenharia do Porto, no departamento de Engenharia Mecânica. O modelo apresentado faz a atribuição das vigilâncias de uma forma hierárquica, utilizando vários critérios, desde a regência da unidade curricular até à simples vigilância. Devido ao facto de estar implementado informaticamente, apresenta reduzidos tempos na formulação e obtenção de uma solução, o que o torna uma boa ferramenta para a criação de cenários alternativos. Em suma, o modelo proposto neste trabalho apresenta soluções de melhor qualidade, em que a distribuição de afetações é proporcional entre os docentes, e o seu tempo de obtenção é muito reduzido em comparação com a alternativa atual.The present study was performed in order to solve the problem of allocating vigilantes to examinations in the Instituto Superior de Engenharia do Porto, in the department of Mechanical Engineering. The model presented makes the allocation of surveillances in a hierarchical manner, using various criteria, since the regency of course to the simple vigilance. Due to it being implemented on a computer, the model presents reduced time in formulating and obtaining a solution, which makes it a good tool for the creation of alternative scenarios. In sum, the proposed model presents better quality solutions, in which the distribution of the affectations is equitable among teachers, and require much less time to obtain compared to the current alternative

An Assignment Problem and Its Application in Education Domain: A Review and Potential Path

This paper presents a review pertaining to assignment problem within the education domain, besides looking into the applications of the present research trend, developments, and publications. Assignment problem arises in diverse situations, where one needs to determine an optimal way to assign n subjects to m subjects in the best possible way.With that, this paper classified assignment problems into two, which are timetabling problem and allocation problem. The timetabling problem is further classified into examination, course, and school timetabling problems, while the allocation problem is divided into student-project allocation, new student allocation, and space allocation problems. Furthermore, the constraints, which are of hard and soft constraints, involved in the said problems are briefly elaborated.In addition, this paper presents various approaches to address various types of assignment problem. Moreover, direction and potential paths of problem solving based on the latest trend of approaches are also highlighted.As such, this review summarizes and records a comprehensive survey regarding assignment problem within education domain, which enhances one's understanding concerning the varied types of assignment problems, along with various approaches that serve as solution

Solving Examination Timetabling Problems through Adaption of Heuristic Orderings

Heuristic ordering based methods, very similar to those used for graph colouring problems, have long been applied successfully to the examination timetabling problem. Despite the success of these methods on real life problems, even with limited computing resources, the approach has the fundamental flaw that it is only as effective as the heuristic that is used. One of the motivations of this paper is to attempt to develop approaches that can operate at a higher level of generality and that can adapt heuristics to suit the particular problem instance in hand

Transformation of the university examination timetabling problem space through data pre-processing

This research investigates Examination Timetabling or Scheduling, with the aim of producing good quality, feasible timetables that satisfy hard constraints and various soft constraints. A novel approach to scheduling, that of transformation of the problem space, has been developed and evaluated for its effectiveness. The examination scheduling problem involves many constraints due to many relationships between students and exams, making it complex and expensive in terms of time and resources. Despite the extensive research in this area, it has been observed that most of the published methods do not produce good quality timetables consistently due to the utilisation of random-search. In this research we have avoided random-search and instead have proposed a systematic, deterministic approach to solving the examination scheduling problem. We pre-process data and constraints to generate more meaningful aggregated data constructs with better expressive power that minimise the need for cross-referencing original student and exam data at a later stage. Using such aggregated data and custom-designed mechanisms, the timetable construction is done systematically, while assuring its feasibility. Later, the timetable is optimized to improve the quality, focusing on maximizing the gap between consecutive exams. Our solution is always reproducible and displays a deterministic optimization pattern on all benchmark datasets. Transformation of the problem space into new aggregated data constructs through pre-processing represents the key novel contribution of this research

Transformation of the university examination timetabling problem space through data pre-processing

This research investigates Examination Timetabling or Scheduling, with the aim of producing good quality, feasible timetables that satisfy hard constraints and various soft constraints. A novel approach to scheduling, that of transformation of the problem space, has been developed and evaluated for its effectiveness. The examination scheduling problem involves many constraints due to many relationships between students and exams, making it complex and expensive in terms of time and resources. Despite the extensive research in this area, it has been observed that most of the published methods do not produce good quality timetables consistently due to the utilisation of random-search. In this research we have avoided random-search and instead have proposed a systematic, deterministic approach to solving the examination scheduling problem. We pre-process data and constraints to generate more meaningful aggregated data constructs with better expressive power that minimise the need for cross-referencing original student and exam data at a later stage. Using such aggregated data and custom-designed mechanisms, the timetable construction is done systematically, while assuring its feasibility. Later, the timetable is optimized to improve the quality, focusing on maximizing the gap between consecutive exams. Our solution is always reproducible and displays a deterministic optimization pattern on all benchmark datasets. Transformation of the problem space into new aggregated data constructs through pre-processing represents the key novel contribution of this research