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Design and Implementation of Mobile Based Students Timetable Management System

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Design and Implementation of Mobile Based Students Timetable Management System

ABSTRACT

Lecture timetabling is a very important process in any educational institution. It is an open-ended program in which courses must be arranged around a set of time slot ’T’ and remains so that some constraints are satisfied.

It constitutes a class of difficult-to-solve optimization problems that lacks analytical solution method. Data gathering on the current system was analysed to create a requirement definition for the improved timetable system.

Literature review was carried out to search the best approach that can help to solve the problem in the timetable system. Genetic Algorithm has been implemented in the Timetable Management System. This is because Genetic Algorithm is able to produce a feasible timetable system.

Java, XML and PHP programming languages were used in developing the solution. MySQL database was used as the back-end for the solution. The front-end solution will be implemented in an android mobile operating system for easier accessibility and proximity to users.

TABLE OF CONTENTS

TITLE PAGE …………………………………………………………………..………. i
APPROVAL PAGE ………………………………………………………………………… ii
DEDICATION ……………………………………………………………………………… iii
ACKNOWLEDGEMENT ……………………………………………………………… iv
ABSTRACT …………………………………………………………………………….. v
TABLE OF CONTENT …………………………………………………………………vi
CHAPTER ONE: INTRODUCTION
1.1 BACKGROUND OF THE STUDY ……………………………………..3
1.2 STATEMENT OF THE PROBLEM …………………………………….4
1.3 OBJECTIVES OF THE STUDY …………………………………………4
1.4 SIGNIFICANCE OF THE STUDY ………………………………………5
1.5 SCOPE OF THE STUDY ………………………………………………..6
1.6 LIMITATION OF THE STUDY …………………………………………6
1.7 DEFINITION OF TERMS ……………………………………………….6
CHAPTER TWO: REVIEW OF RELATED LITERATURE
2.1 REVIEW OF RELEVANT THEORIES AND TECHNOLOGIES ………9
2.2 TIMETABLING AS A NP-COMPLETE PROBLEM ………………….14
2.3 BRIEF HISTORY OF GENETIC ALGORITHMS ……………………..15
2.4 BASIS FOR A GENETIC ALGORITHM ………………………………19
2.5 METHODS OF REPRESENTATION …………………………………..21
2.6 METHODS OF SELECTION ……………………………………………23
2.7 METHODS OF CHANGE ………………………………………………26
2.8 STRENGTHS OF GENETIC ALGORITHMS ………………………….27
2.9 LIMITATIONS OF GENETIC ALGORITHMS ………………………..35
CHAPTER THREE: SYSTEMS INVESTIGATION AND ANALYSIS
3.1 ORGANOGRAM FOR COMPUTER SCIENCE DEPARTMENT …….. 46
3.2 FACTS FINDING …………………………………………………………48
3.3 ANALYSIS ……………………………………………………………….48
3.4 PROBLEM OF THE CURRENT SYSTEM ………………………………49
3.5 PROPOSING A NEW SYSTEM …………………………………………50
3.6 ADVANTAGES OF THE PROPOSED SYSTEM ……………………….50
CHAPTER FOUR: SYSTEM DESIGN
4.1 OBJECTIVES OF THE DESIGN …………………………………………52
4.2 SYSTEM BLOCK DIAGRAM …………………………………………….53
4.3 OUTPUT DESIGN …………………………………………………………54
4.4 INPUT DESIGN ……………………………………………………………54
4.5 PROGRAM DESIGN ………………………………………………………54
4.6 DATABASE ………………………………………………………………..57
4.7 DATABASE SPECIFICATION ……………………………………………57
4.8 PROGRAM FLOWCHART ……………………………………………….58
4.9 MODELLING THE SYSTEM …………………………………………….59
4.10 CHOICE OF PROGRAMMING LANGUAGE ……………………………66
CHAPTER FIVE: SYSTEM DOCUMENTATION AND IMPLEMENTATION
5.1 SYSTEM REQUIREMENTS ………………………………………………67
5.2 HOW TO INSTALL ………………………………………………………..68
5.3 TRAINING OF OPERATORS ……………………………………………..68
5.4 IMPLEMENTATION METHOD …………………………………………..68
5.5 REVIEW AND MAINTENANCE OF THE SYSTEM …………………….70
CHAPTER SIX: CONCLUSION, SUMMARY AND RECOMMENDATION
6.1 SUMMARY ………………………………………………………………………72
6.2 PROBLEMS ENCOUNTERED ………………………………………………….72
6.3 CONCLUSION ……………………………………………………………………72
6.4 CONTRIBUTION TO KNOWLEDGE …………………………………………..72
6.5 RECOMMENDATION ……………………………………………………………73
REFERENCES ……………………………………………………………………………74
APPENDICES …………………………………………………………………………….78

INTRODUCTION

Timetabling concerns all activities with regard to producing a schedule that must be subjective to different constraints.

The 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.

REFERENCES

A. Cornelissen, M.J. Sprengers and B.Mader(2010)”OPUS-College Timetable Module Design Document” Journal of Computer Science 1(1), 1-7.

Abramson D., & Abela J. (1992). “A parallel genetic algorithm for solving the school timetabling problem.” In Proceedings of the 15th Australian Computer Science Conference, Hobart, 1-11.

Adam, M. (2004). “Genetic Algorithms and Evolutionary Computation “.Available online at http://www.talkorigins.org/faqs/genalg/genalg.html.

Al-Attar, A.(1994). White Paper: “A hybrid GA-heuristic search strategy.” AI Expert, USA.

Alberto, C., Marco D., Vittorio, M. (1992). “A Genetic Algorithm to Solve the Timetable Problem”Journal of Computational Optimization and  Applications, 1, 90-92.

Bufe, M., Fischer, T., Gubbels H., Hacker C., Hasprich O., Scheibel C., Weicker K., Weicker N., Wenig M., & Wolfangel C. (2001). Automated solution of a highly constrained school timetabling problem – preliminary results.

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