Optimization of Student Hostel Allocation Using Genetic Algorithms: A Case Study of Federal University, Gusau (Gusau LGA, Zamfara State)
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Background of the Study
The process of allocating hostel rooms to students in universities often faces challenges such as inefficiency, limited space, and lack of transparency. Federal University, Gusau, located in Gusau LGA, Zamfara State, has experienced difficulties in optimizing the allocation of hostel spaces, resulting in unfair room assignments and dissatisfaction among students. Traditional methods for hostel allocation are typically manual and fail to efficiently balance the available space with student preferences.
Genetic algorithms (GAs), a subset of evolutionary algorithms, offer a promising solution for optimization problems. By simulating the process of natural selection, GAs can be used to find optimal or near-optimal solutions in complex environments, such as allocating limited hostel spaces while considering multiple constraints like student preferences, room availability, and fairness. This study aims to apply genetic algorithms to optimize the student hostel allocation process at Federal University, Gusau.
Statement of the Problem
The hostel allocation system at Federal University, Gusau is inefficient, often resulting in delays, unfair assignments, and dissatisfaction among students. Traditional allocation methods do not consider multiple factors, such as student preferences and room availability, in a systematic way. There is a need to explore AI-based methods, like genetic algorithms, to optimize this process and ensure a fairer and more efficient allocation.
Objectives of the Study
1. To design and implement a genetic algorithm-based system for optimizing student hostel allocation at Federal University, Gusau.
2. To evaluate the performance of the genetic algorithm in terms of efficiency, fairness, and student satisfaction.
3. To compare the genetic algorithm-based approach with traditional hostel allocation methods.
Research Questions
1. How can genetic algorithms be used to optimize the allocation of hostel spaces in universities?
2. What are the factors that need to be considered in the optimization of student hostel allocation?
3. How does the genetic algorithm-based allocation system compare with traditional allocation methods in terms of efficiency and fairness?
Research Hypotheses
1. The genetic algorithm-based system will outperform traditional methods in optimizing the allocation of hostel spaces.
2. The genetic algorithm will provide a more efficient and fair solution for student hostel allocation.
3. Students will express higher satisfaction with the genetic algorithm-based hostel allocation system compared to the traditional method.
Significance of the Study
This study will contribute to the improvement of hostel allocation processes at Federal University, Gusau, by providing a more efficient, fair, and transparent system using genetic algorithms. The findings can be extended to other universities facing similar challenges with hostel management.
Scope and Limitations of the Study
The study will focus on the optimization of hostel allocation at Federal University, Gusau, using genetic algorithms. The research will not explore the broader management of university accommodations, such as the construction of new hostels or student welfare outside of accommodation.
Definitions of Terms
• Genetic Algorithm (GA): An optimization algorithm that mimics the process of natural evolution to find optimal solutions to complex problems.
• Hostel Allocation: The process of assigning available hostel rooms to students based on various criteria, such as student preferences and room availability.
• Optimization: The process of making a system as efficient and effective as possible.
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Chapter One: Introduction
