Background of the Study
Exam seating arrangements are a critical aspect of university operations, as they help ensure fairness, minimize cheating opportunities, and comply with university regulations. Traditional manual seating arrangements are often time-consuming, prone to errors, and fail to optimize the available space effectively. Genetic algorithms (GAs), a class of optimization techniques inspired by the process of natural selection, have proven to be effective in solving complex optimization problems, including seating arrangements. By using GAs, it is possible to generate optimized seating plans that minimize conflicts, ensure fairness, and maximize space utilization. This study aims to implement a genetic algorithm to optimize exam seating arrangements at Ibrahim Badamasi Babangida University, Lapai, ensuring that the process is efficient, cost-effective, and fair.
Statement of the Problem
At Ibrahim Badamasi Babangida University, Lapai, the exam seating arrangement process is often done manually, leading to inefficiencies, seating conflicts, and potential violations of regulations. For instance, students who belong to the same group may be seated together, making it easier to collaborate during exams. Additionally, irregularities in the distribution of students across the available seating areas may occur, resulting in suboptimal utilization of resources. Genetic algorithms can provide an automated, efficient, and optimal solution to these challenges, but their potential for improving exam seating arrangements at IBBU has not been fully explored.
Objectives of the Study
Research Questions
Research Hypotheses
Significance of the Study
This study will provide a practical solution to the challenges of exam seating arrangements at Ibrahim Badamasi Babangida University. By implementing genetic algorithms, the university will benefit from more efficient, error-free, and fair seating arrangements. The findings of this study could serve as a model for other universities facing similar challenges, helping to streamline administrative tasks and optimize resource use.
Scope and Limitations of the Study
The study is limited to the implementation and evaluation of a genetic algorithm for exam seating arrangements at Ibrahim Badamasi Babangida University, Lapai, located in Lapai LGA, Niger State. The focus will be on a specific set of exams, and the evaluation will include only students and staff directly involved in the seating process. Limitations include potential resistance to change from administrative staff and the time required for implementing and testing the system.
Definitions of Terms
Genetic Algorithm (GA): A search heuristic that mimics the process of natural evolution to find optimal solutions to complex problems.
Optimization: The process of making something as effective or functional as possible.
Seating Arrangement: The allocation of seats for students during an exam to minimize conflicts and ensure fairness.
Fairness: The quality of being free from bias, favoritism, or injustice in the allocation of seating.
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