Secured Multi-Dimensional Robust Optimization Model for Remotely Piloted Aircraft System (RPAS) Delivery Network Based on the SORA Standard

Abstract

The range of applications of RPAs in various industries indicates that their increased usage could reduce operational costs and time. Remotely piloted aircraft systems (RPASs) can be deployed quickly and effectively in numerous distribution systems and even during a crisis by eliminating existing problems in ground transport due to their structure and flexibility. Moreover, they can also be useful in data collection in damaged areas by correctly defining the condition of flight trajectories. Hence, defining a framework and model for better regulation and management of RPAS-based systems appears necessary; a model that could accurately predict what will happen in practice through the real simulation of the circumstances of distribution systems. Therefore, this study attempts to propose a multi-objective location-routing optimization model by specifying time window constraints, simultaneous pick-up and delivery demands, and the possibility of recharging the used batteries to reduce, firstly, transport costs, secondly, delivery times, and thirdly, estimated risks. Furthermore, the delivery time of the model has been optimized to increase its accuracy based on the uncertain conditions of possible traffic scenarios. It is also imperative to note that the assessment of risk indicators was conducted based on the Specific Operations Risk Assessment (SORA) standard to define the third objective function, which was conducted in a few previous studies. Finally, it shows how the developed NSGA-II algorithm in this study performed successfully and reduced the objective function by 31%. Comparing the obtained results using an NSGA-II meta-heuristic approach, through the rigorous method GAMS, indicates that the results are valid and reliable.

Does intellectual capital reduce the probability of default?

“…These techniques are enormously based on high computing power, which improves the forecasting accuracy of default risk. Mahmoodi et al (2022) suggested the application of a supervised learning method, namely, SVM, for incremental prediction accuracy over ANN. Saffarian et al (2020) indicated that the hybrid model should be taken into account for better risk assessment owing to its flexibility and realism.…”

“…Recently, a series of research studies (Mahmoodi et al , 2022; Mahmoodi et al , 2022, Saffarian et al , 2020; Mahmoudi et al , 2021; Mahmoodi et al , 2022; Mehrjoo et al , 2014) highlighted the importance of intelligent techniques, such as artificial neural networks (ANNs), support vector machines (SVM), fuzzy logic and hybrid models, for measuring default risk. These techniques are enormously based on high computing power, which improves the forecasting accuracy of default risk.…”

Deriving priority vector from pairwise comparisons matrix with fuzzy elements by solving optimization problem

“…[7]. Effectiveness of FAHP together with applications to models in environmental risk assessment and other big projects can be found in [9,16,18,20,21,30]. Such an approach, usually structured to Goal -Criteria -Alternatives, is also well known in the Fuzzy Analytic Hierarchy Process (FAHP) originated by T. Saaty in [29], and also in [10,33].…”

Unmanned Aerial System (UAS) Modeling, Simulation and Control

“…This Special Issue on the "Unmanned Aerial System (UAS) Modeling, Simulation and Control-Part I" focuses on publishing original manuscripts and literature review papers in the areas of UAS modeling, simulation, robust control, artificial intelligent control, design, aerodynamics, aeroelasticity, morphing systems, trajectory optimization, flight tests, wind tunnel tests and other areas closely related to UAS technology improvement. This Special Issue presents research on various UASs and other systems, including the UAS-S45 from the Mexican company Hydra Technologies [1], quadrotors [2,3], drone collision avoidance systems [4], Remotely Piloted Aircraft Systems (RPASs) in [5] and satellite trajectories tracking by radar [6].…”

“…In ''Secured Multi-Dimensional Robust Optimization Model for Remotely Piloted Aircraft System (RPAS) Delivery Network Based on the SORA Standard" [5], a multiobjective location-routing optimization model was proposed for Remotely Piloted Aircraft Systems (RPASs) by specifying time window constraints, simultaneous pick-up and delivery demands, and the possibility of recharging used batteries for reducing the transport costs, delivery times and estimated risks. The model's delivery time has been reduced and thus optimized to increase its accuracy based on the uncertain conditions of possible traffic scenarios.…”