AN INTEGRATED FUZZY ENTROPY AND DIRECTED NETWORK-BASED FRAMEWORK FOR EVALUATING DRONE CRITERIA

The efficient and rapid delivery of health services necessitates optimizing logistics processes, especially for emergencies and rural areas. In this context, drone technologies have come to the forefront in the distribution of medicines and medical supplies in recent years. However, when choosing between drone alternatives, not only technical features but also numerous criteria such as security, cost, operational capability, and environmental factors should be considered. This makes the decision-making process complex and multi-dimensional. In this study, to determine the most appropriate drone alternative to be used in the distribution of medicines in the health sector, the Entropy-based criteria weighting method, Directed Network analysis and Fuzzy Logic Multi-Criteria Decision Making (MCDM) approach were used in an integrated structure. To model uncertainties and differences in interpretation in expert opinions, alternatives were evaluated using Fuzzy Logic. The Entropy method contributed to the weighting process by objectively revealing the information densities of the criteria. Then, Directed Network analysis was applied to determine the interaction and structural priorities between the criteria. To examine the robustness of the proposed model, a sensitivity analysis was performed by varying the parameter that balances entropy-based and directed network. The findings, strong and weak interaction lines within the system, were visualized and the relationships between the criteria were examined in depth.