Timetabling concerns all activities with regard to producing a schedule that must be subjective to different constraints. Timetable can be defined as the optimization of given activities, actions or events to a set of objects in space-time matrix to satisfy a set of desirable constraints.
A key factor in running an educational center or basically an academic environment is the need for a well-planned, well-throughout and clash-free timetable. Back in the days when technology was not in wide use, (lecture) timetables were manually created by the academic institution.
Every school year, tertiary institutions are faced with the tedious task of drawing up academic timetables that satisfies the various courses and the respective examination being offered by the different departments.
Timetable development process starts when each Head of Department provide the following information to be used for timetable scheduling. The information provides the modules with dates, time and venues suitable in a particular semester:
Examinable courses in a particular semester.
Dates for lectures to be held (Lectures can be scheduled between Monday and Friday).
Specified time for lectures ( i.e. Between 8am and 4pm)
The venue of the scheduled lectures.
A timetabling problem consists of four (4) parameters and they are: T (set of time), R (set of available resources), M (set of scheduled contacts) and C (set of constraints). This problem assigns time and resources to the contacts on such a way that the constraints will be satisfied. In various timetabling problems, educational timetabling has been generally examined from practical standpoint. Academic timetable is very crucial but it consumes time due to its frequent occurrences and usage among higher institution of learning. Another reason for the difficulty is because of the great complexity of the construction of size of lectures and examinations, due to the scheduling size of the lectures and examinations periods and high number of constraints and criteria of allocation which is usually circumvented with the use of little strict heuristics, based on solutions from previous year (Jose, 2008).
The quality of the timetable determines the quality of time dedicated by lecturers, students and administrators to academic activities. Various academic timetabling includes:
i. School timetable
ii. Lecture timetable
iii. Examination timetable and
iv. Assignment timetable (Qu, Burke, McCollum, Merlot and Lee, 2004).
This academic timetable must meet a number of requirements and should satisfy the desires of all entities involved simultaneously as wee as possible. The timings of events must be such that nobody has more than one event at the same time (Roberts, 2002).
1.1 BACKGROUND OF THE STUDY
The Department of Computer Science was carved out from the defunct Systems Science (Two departments were created out of Systems Sciences. Computer Science and Mathematics/Statistics) in the year 1997 with Mr. C.J.C. Ayatalumo as her first Head of Department.
The department’s mission and vision are as follows
To procure department portal CNET.
To make the Hardware Maintenance Laboratory fully functional.
To undertake repairs, maintenance, installation, assembling of computers within and outside the institution in order to generate revenue for the polytechnic.
To start off new Computer Engineering Technology Department.
To become Center of Excellence in Computer Science and Engineering.
To resuscitate staff development programmer in the department.
To increase the computing equipment in use in both ND and HND laboratories.
To ensure regular supply of consumables.
Procurement of up-to-date software (licensed).
To provide adequate staff offices and facilities.
Provision of dedicated power supply.
1.2 STATEMENT OF THE PROBLEM
The available system currently builds or generates a set of timetables, but most times have issues with generating a clash-free and complete timetable. The tedious tasks of data introduction and revision of usually incomplete solutions are the bottlenecks in this case (Luisa et.al, 2006). Most educational institutions have resorted to manual generation of their timetables which according to statistics takes much time to get completed and optimal. Even at the optimal stage of the manually generated timetable, there are still a few clashes and it is the lecturer that takes a clashing course that works out the logistics of the course so as to avoid the clash.
1.3 AIM AND OBJECTIVES OF THE STUDY
The literature on and implementation of educational timetabling problem is scattered, vast and far-fetched. Different research papers that have been brought out on timetable may refer to the same type of institution but they mostly deal with different kinds of assignments, i.e. decisions like timing of events, sectioning of students into groups, or assigning events to locations.
Moreover, each institution has its own characteristics which are reflected in the problem definition (Robertus, 2002). Yet, there have been no leveling ground for developing a system that can work for most of these institutions.
The aim of this work is to generate a timetable while demonstrating the possibility of building the schedules automatically through the use of computers in a way that they are optimal and complete with little or no redundancy.
The objectives of this work are as follows
To be able to optimize the algorithm used in today’s timetable systems to generate the best of timetabling data with fewer or no clashes.
To bring approved timetable closer to users especially to those who use android phones.
1.4 SIGNIFICANCE OF THE STUDY
The reasons for this work are outlined below
i. The proposed system will provide an attractive graphical front-end for the administrators and students (mobile platform).
ii. It will improve flexibility in timetable construction.
iii. The system will save time.
iv. Productivity will be improved.
v. The system can be revised i.e. its backend can be revised.
vi. Proper recording of class size, number of courses offered, number and capacity of available lecture halls.
vii. Efficient execution of academic activities.
1.5 SCOPE OF THE STUDY
This study will only cover the management and allocation of spaces and time for lectures in the Department of Computer Science
1.6 LIMITATIONS OF STUDY
The researcher outlined some of the limitations as follows
i. Incomplete data from data collation officers.
ii. Wrong data input from technical user.
iii. Wrong constraint specification.
1.7 DEFINITION OF TERMS
Allocate To set apart for a specific purpose
Android This is a mobile operating system based on the Linux Kernel and currently developed by Google.
Backend Application Serves indirectly in support of front-end services, usually by being closer to the required
resource or having the capability to communicate with the required resource.
Frontend Application This is an application that users interact with directly.
Genetic Algorithm GA is a model of machine learning which derived its behavior from metaphor of the process (es) of EVOLUTION in natural sciences.
Google Cloud Messaging GCM is a tool from Google that allows developers to send data from their server(s) to users’ device(s) and receive message(s) from devices on the same connection.
Hypertext Preprocessor PHP is a server-side scripting language used in building dynamic content for the web.
Extensible Markup Language XML is a language used in designing android layouts.
Timetable This is a table of events arranged according to the time when they take place.