Akademik Veri Yönetim Sistemi
International Journal of Machine Learning and Cybernetics, 2024 (SCI-Expanded)
Unmanned aerial vehicles (UAVs) and their specialized variants known as unmanned combat aerial vehicles (UCAVs) have triggered a profound change in the well-known military concepts and researchers from different disciplines tried to solve challenging problems of the mentioned vehicles. Path planning is one of these challenging problems about the UAV or UCAV systems and should be solved carefully by considering some optimization requirements defined for the enemy threats, fuel or battery usage, kinematic limitations on the turning and climbing angles in order to further improving the task success and safety of autonomous flight. Immune plasma algorithm (IP algorithm or IPA) modeling the details of a medical method gained popularity with the COVID-19 pandemic has been introduced recently and showed promising performance on solving a set of engineering problems. However, IPA requires setting the control parameters appropriately for maintaining a balance between the exploration and exploitation characteristics and does not design the particular treatment and hospitalization procedures by taking into account the implementation simplicity. In this study, IP algorithm was supported with a newly designed and realistic hospitalization mechanism that manages when an infected population member enters and discharges from the hospital. Moreover, the existing treatment schema of the algorithm was changed completely for improving the efficiency of the plasma transfer operations and removing the necessity of IPA specific control parameters and then a novel path planner called hospital IPA (hospIPA) was presented. For investigating the performance of hospIPA on solving path planning problem, a set of detailed experiments was carried out over twenty test cases belonging to both two and three-dimensional battlefield environments. The paths calculated by hospIPA were also compared with the calculated paths of other fourteen meta-heuristic based path planners. Comparative studies proved that the hospitalization mechanism making an exact discrimination between the poor and qualified solutions and modified treatment schema collecting the plasma being transferred by guiding the best solution give a tremendous contribution and allow hospIPA to obtain more safe and robust paths than other meta-heuristics for almost all test cases.