Selection of Military UAV using LMAW and TOPKOR Methods in Neutrosophic Environment

Abstract

Unmanned aerial vehicles (UAVs) are becoming more and more popular as a means of targeting terrorist and insurgent groups across the world due to a rise in terror threats, unconventional military threats, and geopolitical conflicts. The advantages are evident: lower risk to defense personnel's lives, targeted strikes to destroy hostile units, and cost-effectiveness. UAVs may now carry out a wider range of military and homeland security (HLS) missions, including combat strategies, surveillance, and reconnaissance, thanks to technological advancements in the field. UAVs have come a long way from being simple surveillance devices to becoming highly advanced military and peacekeeping equipment. There are various types of military drones, and it is important to have an effective method for selecting the best option for a given situation. In this study, we have introduced the LMAW and TOPKOR methods, which are integrated with the neutrosophic environment to efficiently handle uncertainty and ambiguity in choosing the best military UAV. An empirical analysis of a real-world scenario involving four initial military UAVs, evaluated by four specialists against five criteria, was conducted. The case study demonstrates the effectiveness and feasibility of the proposed evaluation process. We also performed sensitivity analysis and weighted analysis of the alternatives. Additionally, we used CRITIC, ENTROPY, MEREC, RAWEC, VIKOR and ARAS techniques for comparisons.