Enhancing equitable resource allocation: Integrating banker's algorithm with machine learning prediction

Abstract

Global organizations play a pivotal role in tackling some of the world's socio-economic challenges. With well-defined processes, organizations such as UNICEF (United Nations International Children Emergency Fund) make well-informed decisions pertaining to their resource allocation approaches. Although these approaches have recorded some level of efficiency by ultimately allocating resources, they are heavily centered on traditional approaches that fail to reflect the dynamic changes to the growing needs of society due to their static nature. Just like the Public Finance toolkit used by UNICEF, such approaches rely on a paper-like streamlined, human-generated index that determines how allocation works, and this erases the overarching goal of resource allocation, fairness. This capstone focuses on optimizing resource allocation within organizations like UNICEF through the integration of various scheduling algorithms with Banker's algorithm. The goal is to streamline the process of resource allocation right from handling funding requests from the public and subsequently distributing available resources based on pre-defined conditions of the algorithm. The web application relies on PHP-implemented algorithms to manage requests and perform resource allocation to achieve more efficient and transparent results. The system allows organizations to input total available resources and select from multiple scheduling algorithms, including First Come First Serve (FCFS), Priority-Based and Round Robin. The Banker's algorithm is employed to determine the feasibility of each funding request, dynamically updating the request status to either "Accepted" or "Rejected" based on the allocation results. The backend integrates robust database operations to store, update, and retrieve request statuses and allocation details, ensuring data integrity and consistency. User authentication and session management are implemented to secure the application and personalize user experience. This project aims to provide a scalable and efficient solution for resource management in organizations, facilitating better decision-making and enhancing operational efficiency. The system's design and implementation address key challenges in resource allocation, offering a comprehensive tool for managing and optimizing funding requests.