Developing a hybrid continuous-discrete approach for optimizing medical logistics through two-stage location problem solving

Abstract

Optimizing logistics is essential for supply chain management, especially in healthcare. It efficiently distributes medical products efficiently and ensures public health and quick response during crises. Technologies and algorithms, like genetic algorithms for two-stage location problems, improve medical logistics by optimizing facility distribution. This enhances decision-making, speeding up operations and making them more cost-effective.