timetable generator for final year project, Study Guides, Projects, Research of Programming Methodologies

Download timetable generator for final year project and more Study Guides, Projects, Research Programming Methodologies in PDF only on Docsity! TAKORADI TECHNICAL UNIVERSITY FACULTY OF APPLIED SCIENCES DEPARTMENT OF COMPUTER SCIENCE. DESIGNING AND IMPLEMENTATION OF AN AUTOMATED TIMETABLE GENERATOR STUDENT’S NAME INDEX NUMBER A PROJECT REPORT SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE, FACULTY OF APPLIED SCIENCES, TAKORADI TECHNICAL UNIVERSITY IN PARTIAL FULFILMENT FOR THE AWARD OF HIGHER NATIONAL DIPLOMA IN INFORMATION AND COMMUNICATION TECHNOLOGY. DECLARATION We, the undersigned here, declare that this dissertation is entirely our own original work and that, to the best of our knowledge, it has not been presented or submitted for any degree or examination in any other university and that all the sources we have used or quoted have been indicated and acknowledged by complete reference. i ii ACKNOWLDGEMENT First and foremost, we thank the God Almighty, for how far he has brought us and making everything possible for the project to be a success. We have gone through a lot but He has granted us the strength and courage to complete the work. For this, He deserves all the praise and adoration. We would like to express our sincere gratitude to our project supervisor Miss Angela Aba Otchere for the direction, guidance and patience, help, support and invaluable advice, we say God bless you. We would like to extend our gratitude to our parents for supporting us financially and also for your love, God bless you and we love you. v ABSTRACT Creating timetable is tedious and time wasting and sometimes brings various classes clashing either at same venue or with same lectures. The automated time table scheduling provides an easier way for lectures and students to view their timetable once they are finalized over the application, having individual login ID and passwords. The methods used in the design is the Agile mode of system development life cycle the model is a combination of iterative and incremental process models with focus on process adaptability and customer satisfaction by rapid delivery of working software products. Time table generation is tedious job for educationalist with respect to time and man power and further more lack of funds delays in the process of rescheduling the time table whenever they want to solve timetabling problems. The proposed system, "Syllabus and Timetable Generation System” will make the process of timetable generation fast and effective. Most educational institutions have resorted to the manual generation of their timetables which according to statistic stakes 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 to avoid the clash. Therefore, there is a great requirement for an application to distribute the course evenly and without collisions. A simple, easily understandable, efficient, and portable application is developed, which could automatically generate good quality timetables along with their syllabus within seconds. vi TABLE OF CONTENT DECLARATION.............................................................................................................i CERTIFICATION ..........................................................................................................i i ABSTRACT...................................................................................................................iii DEDICATION...............................................................................................................iv ACKNOWLDGEMENT................................................................................................vi TABLE OF CONTENT ...............................................................................................vii LIST OF FIGURES ..................................................................................................... xi CHAPTER ONE ............................................................................................................1 INTRODUCTION ..........................................................................................................1 1.1 Background of the study ...........................................................................................1 1.2 Problem Statement.................................................................................................... 2 1.3 Aim of Study............................................................................................................. 3 1.4 Specific Objectives ................................................................................................... 3 1.5 Research Questions ...................................................................................................4 1.6 Significance of the Study ........................................................................................ 4 1.7 Limitations ............................................................................................................... 5 1.8 Delimitations ......................................................................................................... 5 1.9 Organization of the study .................................................................................... 6 vii Figure 3. Sequence Diagram to show how the different objects interact during the execution of the system. Field work, 2022. ................................................................. 41 CHAPTER FOUR........................................................................................................ 41 RESULTS AND FINDINGS....................................................................................... 42 4.1 Results and Findings from the Research Instruments......................................... 42 4.2 Discussion of the Results/Findings With Respect To Research Questions ........... 43 CHAPTER FIVE.......................................................................................................... 45 SUMMARY, CONCLUSION AND RECOMENDATION ....................................... 45 5.1. Summary...................................................................................................................... 45 5.2. Conclusion ................................................................................................................ 45 5.3. Recommendations .................................................................................................... 46 5.4. Future Research........................................................................................................ 46 REFERENCES......................................................................................................... 47 APPENDIX A........................................................................................................... 50 SECTION A: BIODATA .......................................................................................... 50 SECTION A: AUTOMATED TIMETABLE ACCEPTANCE................................ 51 APPENDIX B: .......................................................................................................... 53 Codes x xi LIST OF FIGURES Figure 3.1: Systems Development Life Cycle.................................................................5 Figure 3.2: Time Table Dashboard Interface, field work. 2022....................................13 Figure 3.3: Use Cases Diagram Field Work, 2022........................................................15 Generate Timetable.......................................................................................................17 Figure 3.4: Sequence Diagram to show how the different objects interact during the execution of system.......................................................................................................17 xii in the time table. For example when I.T 3A has system administration at 9:00am at OBFF1 and I.T 3B has E-commerce at 9:00am at the same OBFF1 we then say that the classes have clashed. The current timetable system used now does not guarantee a clash-free timetable. This also brings a delay in completing timetable. 1.3 Aim of Study The main aim of this study is to develop a simple, easily understandable and efficient software which could automatically generate good and quality time tables for Takoradi Technical University. 1.4 Specific Objectives The objectives of this study are to: • Improve security • Eliminate clashes in timetable • Eliminate errors in timetable 1.5 Research Questions Will the automated time table be able to minimize clashes of classes in a particular department? Will the automated time table be able to eliminate errors? Will the automated time table be secured? 3 1.6 Significance of the Study There are some benefits the study will bring to the school system and improve quality of the system and they are: It will provide an easy means for data entry and revision through an intuitive interface: the software will have a database that will contain data like the name of lectures, the course, room and the time allocation. When the lecture want to create timetable, because of the database the system will easily allocate the lectures, the course, time and the room with the information provided in the database. The system will offer flexibility: changes can be done easily when there is a need of change in the timetable. If a lecture wants to change the time or place for his course, he will then go to the time table and make his changes. It will utilize minimal processing/computing power; the time table will use less computing power when creating and implanting it. This is because the time table will allocate the courses, time and venue automatically with the help of the database provided for the system and will not need extra computing power in using it. 1.7 Limitations • Access of internet connectivity Limited information about the proposed system 1.8 Delimitations • Our research will only be focus on creating an automated time table for lessons done in a class. 4 • The time table will be created for only IT department because of limited time for the project. 1.9 Organization of the Study This report will contain five chapters, chapter 1 will introduce the reader what we are doing as a project work. We will also discuss the background of our study; in this we will discuss what Automated Time Table means, the problem statement at hand and what we are going to do to solve that problem. We will also discuss our main aim and objectives, we will list some research questions, limitation, delimitations and our organization of study. Chapter 2 will be our literature review, we will discuss what people have done based on our topic and state the weakness in their own project. We will also discuss how our project will try and to eliminate these weakness in the other projects. Chapter 3 will be our methodology; we will discuss our research design type, our population and sample size, number of participant sampled and how our sampling will be done. We will discuss the instruments used for to collect the data. We will give reasons for the instruments used. We also discuss the procedure we used for data collection and our data analyses plan. Chapter 4 is our result of the research we did in chapter 3 and we also got our findings with respect to the research questions. Chapter 5 will be a summary of our key findings from our research in all the previous chapters. We will then conclude of all what we have said from chapter1 to chapter 4. We also make recommendations. There will be references on the websites we visited for our results and findings, then we have our appendices. 5 (1960s) and were developed by Holland (1975) and his students and colleagues at the University of Michigan in the (1960s) and the (1970s.) Holland's Genetic Algorithm is a method for moving from one population of chromosomes to a new population by using a kind of natural selection together with the genetics inspired operators like crossover, mutation, and inversion. A chromosome contains a group of numbers that completely specifies a candidate solution during the optimization process. The idea of using a population of solutions to solve practical engineering optimization problems was considered several times during the (1950's) and (1960's). However, the concept of Genetic algorithms were essentially invented by one man—John Holland—in the (1960's.) His reasons for developing such algorithms were to solve problems of generalized concerns. He itemized this concept in his book in (1975,). Its application has proven it to be more than just a robust method for estimating a series of unknown parameters within a model of a physical system. However its robustness cuts across many different practical optimization problems especially those that concern us most like the timetable problem in the context of this project. According to Kong & Kwok (1999), timetabling system involves a heuristic function to increase the scheduling performance, as well as producing a best outcome. Currently, the well-known solutions for the timetabling system are Genetic Algorithms and Memetic Algorithms Mohd. Dain, Shaari, Gom & Bacheck (2001). However, Causmaecker and his friends introduced the Semantic Web as a solution in the domain of timetabling. Berger & Barkaouia, M. (2002) also introduced a Parallel Hybrid Genetic Algorithm for the vehicle routing problem, which they argues to be faster, more cost-effective and highly competitive than the best- known heuristic routing procedures and solutions. Obviously, researchers are still looking 8 forward to heuristics that are suitable for their particular problems (Causmaecker, Demeester & Vanden (2002). On the other hand, there are many solutions for the timetabling system, while each of them has their strengths and weaknesses. 2.1.2 Reviewed Existing Theories Solutions to timetabling problems have been proposed since the 1980s. Research in this area is still active as there are several recent related papers in operational research and artificial intelligence journals. This indicates that there are many problems in timetabling that need to be solved in view of the availability of more powerful computing facilities and advancement of information technology (Deris, 1997). The problem was first studied by Gotlieb, (1962), who formulated a class-teacher timetabling problem by considering that each lecture contained one group of students, one teacher, and any number of times which could be chosen freely. Since then the problem is being continuously studied using different methods under different conditions. Initially it was mostly applied to schools. Since the problem in schools is relatively simple because of their simple class structures, classical methods, such as linear or integer programming approaches Tripathy, (1984), could be used easily. However, the gradual consideration of the cases of higher secondary schools and universities, which contain different types of complicated class-structures, is increasing the complexity of the problem. As a result, classical methods have been found inadequate to handle the problem, particularly the huge number of integer and/or real variables, discrete search space and multiple objective functions. This caused the weakness in this theory. As mentioned earlier the creation of a timetable is very complex. The problems in timetables have been constructed by hand and then modified each semester and each year. It is known that the time, required for solving this type of problems increases 9 exponentially with the problem size. In order to generate this type of schedules we must choose the right optimization techniques that produce optimal solutions in an acceptable time depending on size because the usage of many dimensions increases the time needed for creating the schedule. The most efficient and powerful method for minimizing timetabling conflicts and solving this type of problems are genetic algorithms. Genetic algorithms are general search and optimization algorithms inspired by processes and normally associated with the natural world. 2.1.3 Hard Constraints Involved In Existing System Hard constraints are the one’s which needs to be fulfilled necessarily. No participant can be in more than one room at same time: the timetable created by Gotlieb made sure that participants (lectures and students) have not been allocated in more than one room at the same time. One room to a class at a particular time. No room should be doubled booked, each room should be booked once at a particular time. The class allocated to a particular room have to be a group of students in the same class, offering the same course and the same lecture. The room capacity should be large enough to contain the students. The time should indicate that the room allocated is large enough to contain the students. The number of students are to known and the timetable should indicate the room which can contain the whole class 2.1.4 Soft Constraints Involved In Existing System Soft constraints: These are the constraints that are not that obvious but still demanding. They are not to be really satisfied but the solutions are generally considered good if large numbers of them are taken care. 10 Genetic algorithm is a metaheuristic motivated by the procedure of natural selection that belong to the bigger class of evolutionary algorithms (EA). Genetic Algorithms are motivated by Charles Darwin’s evolutionary theory. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation (Vijini Mallawaarachchi (September 2020). Genetic Algorithms comes below the class of Evolutionary algorithms that use the Principle of natural collection to develop a set of solution towards the best result. It is a search heuristic which Generates solutions to optimization problems using Technique motivated by natural evolution like mutation, Inheritance, crossover and selection ( Kavya Reddy, & Panimozhi, (April 2015). However its robustness cuts across many different practical optimization problems especially those that concern us most like the timetable problem in the context of this project. These foundational works established more widespread interest in evolutionary computation. By the early to mid-1980s, genetic algorithms were being applied to a broad range of subjects, from abstract mathematical problems like bin-packing and graph coloring to tangible engineering issues such as pipeline flow control, pattern recognition and classification, and structural optimization (Goldberg, 1989). When using Genetic algorithm, the number, or population, guesses the solution to the problem. When you building the time table the number of students is very important in implementing a timetable. If the number of students are large it should indicate that the lecture hall is too small to contain the students and also locate them to another room which can contain them. Also, a way of determining the states of generated solutions i.e. calculating how well or bad the individual solutions within the population are, is also considered when using Genetic algorithm. 13 Again, Genetic Algorithm is a method for mixing fragments of the better solutions to form new, on average even better solutions. Last but not the least, Genetic Algorithm is a mutation operator to avoid permanent loss of diversity within the solutions. An advantage of Genetic Algorithm is that it provides diverse values solutions and reaches global maxima. Maturation is used to induce diversity. Saving best solution is helpful. 2.2.2 Review of Different Algorithms For the past years, the problem of educational time table scheduling using different algorithms have been solved by several people. The following are some related works Fang (1994) in his doctoral thesis, investigates the use of genetic algorithms to solve a group of timetabling problems. He presents a framework for the utilization of genetic algorithms in solving of timetabling problems in the context of learning institutions. This framework has the following important points, which give you considerable flexibility, a declaration of the specific constraints of the problem and use of a function for evaluation of the solutions, advising the use of a genetic algorithm, since it is independent of the problem, for its resolution. Fang, (1994) during his doctoral thesis found out the use of Genetic Algorithm (GA) in solving range of timetabling and scheduling problems. He said that GA is suitable, useful and successful alternative for solving such problem which is very hard in general. The framework enables GAs to solve modular timetable problem in Educational institutions. His approach included some components: The declaration of problem specification constraints. Construction of problem specific evaluation function and using a problem independent Genetic Algorithm to attempt to solve the problem.(Holland,1970). 14 The general analysis of reliability and robustness of the approach is conducted and successfully results are demonstrated. The success of his approach relies on the use of special designed mutation operators which greatly upon the performance of Genetic Algorithm with standard operators. The proposed system will be developed to provide an easy means for data entry and revision through an intuitive interface. Eley (2006) in PATAT presents a solution to the exam timetable problem, formulating it as a problem of combinatorial optimization, using algorithms Ant to solve. Analyzing the results obtained by the various works published, we can say what the automated generation of schedules is capable of achieving. Some works show that when compared with the schedules manuals in institutions of learning real, the times obtained by the algorithms for solving the class-teacher timetabling problem are of better quality, since, uses some function of evaluation. The proposed system will be developed to solve the crashing of classes in study halls and provide information on available halls. This will help to eliminate the delay in classes due to unavailability of lecture rooms. Fernandes (2002) classified the constraints of class-teacher timetabling problem in constraints strong and weak. Violations to strong constraints such as schedule a teacher in two classes at the same time result in an invalid timetable. Violations to weak constraints result in valid timetable, but affect the quality of the solution for example, the preference of teachers for certain hours. The proposed algorithm, evolutionary, has been tested in a university comprising 109 teachers, 37 rooms, 1131 a time interval of one hour each and 472 classes. The algorithm proposed in resolving the scheduling without violating the strong constraints in 30% of executions. The proposed system will be developed to inform the user when a class is occupied at a particular period of time and also providing information on assigned teachers to avoid double assigning of teacher to a course. Srinivasan, Tian and Jian (2002) worked on automated time table generation using multiple context reasoning for university modules. The paper presented an evolutionary 15 sure that there another timetable, but with the automated time table you can easily make changes in few minutes. 2.4 Limitations of the Existing System The traditional generations of timetables encounters a lot of problems which may include the following: The existing time table may not be useful in the future. The existing time table may be useful now but may not be useful in the future because of the changes of lectures, courses, places and time allocation so every semester there will be the need of creating another time table. Final generated timetable may not be near optimal as a result of clashing course requirements and allocations. The final generated time table will be full of clashes because the time table will not alert the lecture that there is a class at where he want to place his class in respective of the place and time. It generates a lot of paperwork and is very tasking: the existing time table is a paper work and any paper work is very tasking. When you make a mistake on a paperwork, you have to create the whole thing again on another paper. It is not flexible as changes may not be easily made: changes in time table is not flexible or easy when it is a paper work. You have to cancel the whole thing and create another one when there is a mistake somewhere. 2.5 Some Gaps and Weakness in the Previous Study The sample size used in the previous study was based on only students in universities. The previous studies based their research only on the students in the universities. This does not 18 guarantee accurate sample size because time table is use in all levels of education. So the research should done in all the levels of education. The genetic algorithms used in the above systems was complex to implement. The above system was very difficult to understand. They may not always find the optimal solution to the problem. The genetic algorithms used in the above systems was difficult to debug. They can be difficult to debug and can be computational expensive. They can be sensitive to the initial conditions and can sometimes converge to local optima. The genetic algorithms used in the above systems was slow. Genetic algorithms is a slow gradual process that works by making slight and slow changes compared other algorithms. Generic algorithms are also difficult to optimize. They can be time consuming to run. Additionally they may not find the global optimum and can be stuck in local optima. 2.6 Advantages of the Proposed System The timetable generation process by the education centre staff is: Unlike the current timetabling system, the proposed system will offer flexibility: the automated time table is very flexible, changes can be made easily whenever there is a mistake in the timetable. The automated time table will automatically take note of all the mistakes being it spelling mistakes and other mistakes and these mistakes will be corrected in a few minutes. Even if there are no mistakes and the lecture wants to make some changes it is very easy. It will greatly reduce the time needed to generate near-optimal timetables: in automated time table there is no need for creating a timetable over and over again. Changes can be made every semester to create new time tables, with one time table, 19 It will provide an easy means for data entry and revision through an intuitive interface. With the help of a database, the entry of data will be simple, the database will store data used in the timetable. Data like name of lecture, courses, time and venue. It will simplify the timetabling process. The process in timetabling will be simple in timetabling process. When creating the timetable the process will not be complex. It will provide automatic time table scheduling. Automatically create and maintain academic schedules of students within minutes. Automated Timetable Management System allows you to easily create a unique timetable for each class and subject. Generate reports for different periods and automatically calculate absences. Generate Multiple Timetables. Create multiple timetables at a time and manage different timetable databases for multiple departments with customizable notifications and alerts. The software will provide a high sense of security. This software will require the use of password which is highly secure with role-based permissions and privileges to provide restricted access to users and ensure transparency. Strict privacy and confidentiality of information is protected. The timetable will be Intuitive & User-friendly. Timetable Management Software is simple and easy to use. When a new user uses the system for about one week to two weeks he/she will be able to familiarize with the system because no technical knowledge is required to operate it. Very easy to implement in institutions of any type or size. The timetable will reduce error. There are human errors in any manual process. Using the automatic time table the chance of failure is small. The error-free method of creating a timetable will prove to be a blessing for the school with multiple class levels, with many class divisions. Instance notifications for changes. Using an automated timetable makes it easier for students to receive immediate updates in the event of change in timetable, such as shift of class time or 20 traits including a focus on asking people questions in a standardized manner, the use of a standardized set of questions, and the use of standardized methods of data analysis. 3.2.1 Reasons for Using Questionnaires There are several advantages that researchers may consider while selecting a questionnaire as their preferred data collection tool. They are as follow. •In questionnaires more information is obtain due to the large number of responders. Because it is on the internet a lot of people get the chance of answering the questions when it is online questionnaires. • Broad coverage: people can answer questionnaires no matter how far they are, with the use of internet. Today people sit comfortably in their homes and answer questionnaires without stressing. This makes the questionnaires free and fair. • There is a sense of honesty in questionnaires and anonymous: when people answer questionnaires they have some confident because there is no interference from the one who is asking the questions, after all he or she will not give out his or her name for the receiver to ask him/her why he/she said this or that • Questionnaires does not consume time when filling. When filling questionnaires is very easy to understand because is involve the state the responders are in so much time is not wasted. 3.2.2 Data Collection Procedure In using questioners in our research, we used the structure form of questioners, in which we had definite questions. With structures questioners, questions are presented exactly the 2 same wording and in the same order for all responders. The questions will be only closed questions. The responders will either choose from the options provided. We set questions based on the information we want to get from the lectures and students in the IT department, we printed the questionnaires and shared it for them to answer the questions. We collected them back and analyzed the answers. 3.3.1 Research Design Research design is the framework of research methods and techniques chosen by a researcher to conduct a study. The design allows researchers to sharpen the research methods suitable for the subject matter and set up their studies for success. A research design is a broad plan that states objectives of research project and provides the guidelines what is to be done to realize those objectives. It is, in other\words, a master plan for executing a research project. There are many research design type used in research but the one we used in our research was the questioner’s research. A Questioners research refers to a particular type of research design where the primary method of data collection is by questioners. In this study design, questioners are used as a tool by researchers to gain a greater understanding about individual or group perspectives relative to a particular concept or topic of interest .A questioners typically consists of a set of structured questions where each question is designed to obtain answers. A questioners is a research method used for collecting data from a predefined group of respondents to gain information and insights into various topics of interest. 3 3.3.2 Research Methodology The methodology that is used is the design methodology Agile Methodology. Agile SDLC model is a combination of iterative and incremental process models with focus on process adaptability and customer satisfaction by rapid delivery of working software product. Agile Methods break the product into small incremental builds. These builds are provided in iterations. Each iteration typically lasts from about one to three weeks. Every iteration involves cross functional teams working simultaneously on various areas like. 4 efficient solutions to them. Flexibility also allows project teams to respond to customers and improve the product. Also, the model Improves Project Predictability: Higher visibility during a project execution makes it easier to predict risks when they show up. Predicting risks will in turn give you the chance to craft mitigation plans on how to analyze different risks and avoid the bad ones. The agile methodology presents even greater ways to identify risks, protect, and manage risks. One benefit of identifying risks beforehand is that it enables the smooth operation of the project. A project operation can go south when the team faces unprepared risks during any phase of the project management life cycle. Cost control: An agile method can also be used to improve cost control. After each stage, the team reviews the budget when making future decisions. Then, they decide if they will continue, suspend or cancel tasks or even the project itself. This is an essential part of project management as it allows teams to understand the costs of each feature, which will then be taken into account when making strategic decisions. Stake holders’ engagement: A key part of using an agile method is the involvement of stakeholders when completing projects. By collaborating with different stakeholders during each phase of the project, you will build a dynamic system based on the trust and confidence of each team member and forge greater and stronger relationships within your teams. To use this method effectively, it is recommended to have stakeholders participate actively as the project progresses. This will allow them to make sure that tasks are being completed according to the plan and make changes if necessary. Complete visibility of the progress of each project in real-time: Another advantage of using an agile approach is the transparency of each project thanks to feedbacks due to frequent exchanges with clients. This allows them to feel more involved and ask for changes throughout the project. Moreover, the teams that are involved can show their progress to the client along with the obstacles that they have encountered. This establishes 7 a relationship of trust and collaboration between the team and the client, and can lead to improved customer satisfaction and higher business value. Speed and flexibility: another benefit of using agile is its speed and flexibility thanks to a Scrum framework. This practice places change at the heart of its development. If there is a deviation from the initial objectives, the approach and processes are immediately adapted to meet the new needs and requirements. The Scrum method was originally designed for software development teams and their technical projects. However, today, it can be used for a wide range of projects, especially in marketing. Scrum is one of the most used agile methods because it can be set up very quickly. Furthermore, it is based on an empirical approach, which allows the method to make room for changes as your project grows. Improves quality: Testing is a vital process under the project execution phase when using the agile methodology. This process ensures the best quality for the final product. During the execution or development phase, the client will be actively involved. The client can also ask questions based on realities in the market. This process is repetitive, enabling the project team to keep learning new processes while executing the project. Self-organization helps the team to grow and improve even while working on tasks. For the agile method, the projects are attended to incrementally because it makes them manageable. Also, when using an agile methodology, teams can break down projects into sprints and collaborate with one another to provide high quality results. This method allows teams to deal with common project pitfalls such as managing costs, scope creep and not respecting deadlines. Moreover, there is a testing phase for every task, which allows teams to identify and focus on solving issues quickly to avoid any long term negative consequences. Last but not least, attending to projects in small stages makes it easier to reflect changes in the project management life cycle. If you use some other approach, it might be difficult to detect issues during project implementation. Another approach to project management 8 may not give your team any chance to make corrections until the project is completed (Belyh, 2022). 9 will be space for the user to add a school in order to create the timetable for, and the school’s name will then be saved in the database. (ii) Department This section has thirteen departments. In this case after selecting the school you want to create the timetable for. In case the department you want to create the timetable for is not in the system there will be space for the user to add a department in order to create the timetable for, the department’s name will then be saved in the database. (iii) Student In this section it has five students groups where the students’ details are recorded. (iv) Class timetable This section is where timetable for a class is created, in this the class is selected and the timetable is created for the class. (v) Exam Time Table This section is where exam timetable for a class is created, in this the class is selected and the exam timetable is created for the class. (i) Note This section gives any further notifications about the timetable, if there is any message the lecture wants the students to know the lecture will indicate in the time table. 12 Figure 3.2: Time Table Dashboard Interface, field work. 2022 The interface The Admin has full control of the system, all the functions are to be performed from Admin panel. Here, the admin can set different schedules easily. In order to set schedules, the user has to select Faculty, Course, Subject, and Room, enter start and end time. The user has to insert details on each and every module 3.4.3 Systems Design System design is the specification or construction of a technical, computer-based solution for the business requirements identified in a system analysis. It gives the overall plan or model of a system consisting of all specifications that give the system its form and structure i.e. the structural implementation of the system analysis. 13 3.4.4 Modelling the System Modeling a system is the process of abstracting and organizing significant features of how the system would look like. Modeling is the designing of the software applications before coding. Unified Modeling Language (UML) tools were used in modeling this system. 3.4.5 Unified Modelling Language (UML) Modelling The Unified modeling language is an object-oriented system notation that provides a set of modeling conventions that is used to specify or describe a software system in terms of objects. The Unified Modeling Language (UML) has become an object modeling standard and adds a variety of techniques to the field of systems analysis and development hence its choice for this project. 3.5 Use Case Diagram Use case diagrams describe what a system does from the standpoint of an external observer. The emphasis of use case diagrams is on what a system does rather than how. They are used to show the interactions between users of the system and the system. A use case represents the several users called actors and the different ways in which they interact with the system. 14 MESSAGES • Invoke • Specify Input • Input Buildings Input Halls • Input Programs • Input Lecturers • Input Courses • Add Input • Set. allocations 17 Generate Timetable Figure 3.4: Sequence Diagram to show how the different objects interact during the execution of system Field work, 2022. 18 CHAPTER FOUR RESULTS AND FINDINGS 4.1 Results and Findings from the Research Instruments In the previous chapter, we discussed about the instruments used for the research , As it was discussed earlier, questioners was used in the research and some questions was set on paper and printed for people to answer. The questions were based on the information we wanted to get, the people who answered the questions were students from the Information Technology Department. In our questioners, we asked the student and again we asked if there are any challenges in the current timetable system, and there was an agreement that there are some challenges in the current timetable system. We then asked the challenges they face in current the time table, some said the room allocated to them on the timetable would be occupied by other people from a different class at the same time they have class, others were saying that sometimes the lectures would have class with other group at the same time they have class with him or her. Also, others were saying that sometimes they would have two courses at the same time. Also, we asked what the lectures do when there is a problem in the timetable system, some said the lecture schedule another time to meet them, others said the give them note and forget about meeting them, Others said the lecture do online classes with the and also others said they add them to another class. Furthermore, we asked what the school authoritative have done about the problem, and they said they make changes whenever there is clash in the timetable. Others said they create new time tables over and over again. People said they feel sad about the problems in the current timetable system, others feel board. They also said the current timetable system is not easy to implement, changes are 1 CHAPTER FIVE SUMMARY, CONCLUSION AND RECOMENDATION 5.1. Summary This study was carried out to reduce the intense manual effort being put into creating and developing timetables. The timetable automation system currently is a conceptual work in progress but has the capability to generate near optimal timetables based on two unit courses with minimized course constraints. 5.2. Conclusion Timetabling problem being the hard combinatorial problem that it is would take more than just the application of only one principle. The timetabling problem may only be solved when the constraints and allocations are clearly defined and simplified thoroughly and more than one principle is applied to it i.e. a hybrid solution (a combination of different solution techniques).This research has been able to actualize a sub-implementation of a genetic algorithm which can be applied to input of 2-units Courses. 5.3. Recommendations 1. This system should be implemented to replace the existing timetable system to avoid slot clashes when framing timetable. 2. When implemented, it will help reduce time consumption in generating timetable. 5.4. Future Research For a fully functional system, the genetic algorithm should be fully implemented by satisfying the following objectives: 4 • The timetable system developed as the outcome of this project should be made open to avoid students of computing who can collaborate and improve on the techniques and ideas inherent in this project. • Further works on developing a timetabling system should be based on this research work so as to utilize the incremental model of software development. • A collaborative model of timetabling system which utilizes a computer network can also be built which entails different departments and entities allocating courses and constraints concurrently while the system threads and reports clashes. REFERENCES Alberto, C. (1992). "A Genetic Algorithm to Solve the Timetable Problem" Journal of Computational Optimization and Applications, 1, 90-92. Ansari, A., & Sachin, B. (2012). Genetic Algorithm to Generate the Automatic Time- Table – An Over View. Bachelor, J. (1985). Management Information System, Daily Improvement Vol 6, Pg. 44. Deris, B. (1997). "University timetabling by constraint-based reasoning: A case study". Journal of the Operational Research Society, 48(12), 2-4. Eley, M. (2006). "Ant Algorithms for the Exam Timetabling Problem". 6th International Conference on the Practice and Theory of Automated Timetabling, PATAT'06. 5 Fang, H. L. (1994). "Genetic Algorithms in Timetabling Problems". PhD Thesis, University of Edinburgh. Fernandes, C. (2002). "Infected Genes Evolutionary Algorithm for School Timetable". WSES International Conference. Goldberg, D. (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley. Gotlieb, C. C. (1962). "The construction of class-teacher timetables." Proceedings of IFIP Congress, North-Holland Pub. Co., Amsterdam, 73-77. Holland, J. (1975). Scheduling, Adaptation in Natural and Artificial Systems. The University of Michigan Press. https://www.youtube.com/watch?v=RGb5ciD6PuE (Project worlds, online examination PHP and MY SQL). John, H. (1992). "Genetic algorithms." Scientific American, 66-72. Lawrie, N. L. (1969). "An integer programming model of a school timetabling problem." The Computer Journal, 12, 307-316. Robertus, J. W. (2002). School timetable construction-Algorithm and Complexity, 1st ed. Netherlands: University of Eindhoven Press. 6 C. HND [ ] D. BTECH [ ] SECTION A: AUTOMATED TIMETABLE ACCEPTANCE Strongly Agree (SA), Agree (A), Disagree (D) Strongly Disagree (SD) and Neutral (N) SA A SD D N 4) The current timetable have some challenges 5) The most challenge in the current timetable is clashes of classes 6) When there is a clash in timetable lessons go on 7) Lectures and students get worried when there a clash in the timetable 9 the clashes in timetable 9) Students feel sad when there is a problem in timetable 10) The current system automatically schedule timetable 8) Authorities have tried to come up with a solution to avoid APPENDIX B: Program Listings 10  Ce ee J Asem «nytt esenstfhatrame, Suterninn, Soneuied, daemons); 2H Setlow =" oben 2 suacsavd = mys atch aroyreni) Sheer 7 | Seotns = tptonn epee fats 11 pres Roane! 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