A novel integrated multi-criteria decision making approach for solving delivery drone selection problem

Due to rapid advancements in microelectronics and computerization, drones are being widely used, and have gained significant attention in multiple military, industrial and commercial applications. Selection of the most appropriate drone for a specific application, especially for delivery operation, appears as a challenging task, and can be treated as a typical multi-criteria decision making (MCDM) problem due to presence of numerous choices available in the market and set of conflicting criteria. To resolve the issue, this paper proposes application of a novel MCDM approach hybridizing symmetry point of criterion (SPC) with preference ranking on the basis of ideal-average distance (PROBID) and its simple variant sPROBID. Its effectiveness is demonstrated based on an illustrative example consisting of eight delivery drones and eight evaluation criteria. The SPC method identifies ‘cost’ and ‘maximum speed’ as the most important and least important criteria respectively, while Power Vision Power Eye drone is identified to be the best choice using both PROBID and sPROBID methods. The corresponding statistical tests (Spearman’s rank correlation and Kendall’s tau-b) validate solution accuracy and reliability of the proposed approach against other popular MCDM techniques. Furthermore, sensitivity analyses with respect to variations in criteria weights prove robustness of this approach. Thus, it can serve as a viable MCDM tool for effectively identifying the most suitable drone for a given delivery operation from a large number of feasible options leading to faster delivery, higher efficiency with reduced operating cost, minimum environmental impact, increased accessibility and improved inventory management, resulting in sustainable supply chain management.