Evaluation of Path Planning Algorithms Based on AHP-CRITIC Comprehensive Assignments

This paper addresses the limitations of existing evaluation methods for UAV path planning algorithms, such as subjectivity and lack of accuracy. By integrating the Analytic Hierarchy Process (AHP) and the CRITIC weighting method, a comprehensive evaluation framework is proposed. The framework combines qualitative insights from AHP and quantitative analysis from CRITIC to objectively and thoroughly assess algorithm performance. The study evaluates four critical dimensions of UAV path planning: algorithm effectiveness, stability, convergence, and path safety. Experimental results demonstrate the robustness of the proposed methodology through the evaluation of particle swarm optimization (PSO) and genetic algorithms (GA) under complex environmental and UAV constraints. The findings highlight the framework’s ability to mitigate subjective biases, improve result credibility, and adapt to large-scale scenarios, making it a valuable tool for performance assessment in UAV applications.