AI-based optimization of packing problems for enhancing medical safety systems

Abstract

In the context of enhancing medical safety systems, AI-based optimization of packing solutions is crucial, particularly in the secure and sanitary storage of hazardous materials within healthcare environments. Ensuring that toxic, radioactive, or infectious substances are stored according to strict sanitary guidelines is vital for protecting public health and preventing contamination. This study introduces an AI-driven mathematical model to address packing problems, with a focus on meeting both technological and hygiene standards. By modeling the optimal placement of containers in a deployment area and incorporating key safety and sanitary restrictions, the problem is reduced to a nonlinear programming framework. The phi-function technique is utilized to capture geometric relationships effectively, enabling the development of AI-optimized, sanitary-compliant storage solutions. Numerical examples are provided to demonstrate the approach's efficacy.