Intelligent Scheduling Algorithms for the Enhancement of Drone-Based Innovative Logistic Supply Chain Systems

The integration of advanced technologies such as artificial intelligence, the Internet of Things, and location-tracking technologies has revolutionized our daily lives by enhancing the functionality of logistical services. However, these advancements have also placed significant pressure on the current supply networks and have impeded further growth within the logistics industry. This article presents an inventive logistic supply chain solution utilizing drone-based delivery to tackle the logistic supply chain issues. The proposed solution goal is to minimize the maximum required time to finish all assigned delivery tasks. A set of sophisticated algorithms was developed based on the combination of dispatching rule, randomization, and iterative methods to optimize the performance of the supply chain processes and effectively accomplish the aim of time savings. The deployed system enables the management of a larger volume of shipments and increases the efficiency of logistic supply chain management. The experimental results demonstrate that the proposed algorithms can decrease the maximum duration required to complete the delivery operations assigned to the drones in 1520 cases. The algorithm that exhibited the highest level of performance was the $MID$ algorithm, which attained a staggering percentage of 87.7%, an average deviation from the optimal solution of 0.001, and an execution time of 0.0215 s. Moreover, after comparing their outputs, the $MID$ algorithm was determined to outperform the top two algorithms in the literature.