Development and implementation of an optimization model for the assignment of medical specialties in clinics: application of the Knapsack algorithm with a graphical interface in Python

Abstract

This project presents the development and application of an optimization model designed to allocate medical specialties to clinics based on a predefined schedule. By employing the Knapsack algorithm in Python, the model aims to optimize resource utilization within a medical environment, ensuring that the distribution of services is both efficient and effective. The model incorporates critical constraints such as clinic capacity and patient service demand, which are essential for balancing resources across various specialties. Furthermore, the model addresses potential scheduling conflicts, ensuring that no overlaps occur among different specialty professionals assigned to the same clinic. The integration of these constraints ensures that the allocation process is not only optimal but also practical for real-world implementation. The results demonstrate the potential of this approach to enhance operational efficiency, minimize resource wastage, and improve patient care by strategically managing the availability of specialized medical services across clinics. This model serves as a robust framework for healthcare organizations aiming to improve their resource management strategies.