摘要
Five-axis flank milling is an advanced machining technology widely employed for producing complex geometries, where tool path planning directly influences surface quality and machining efficiency. However, the mathematical nature of the problem presents a large-scale global optimization challenge, involving the search for optimal solutions within a high-dimensional decision space. To address this issue, this paper provides a review of eight state-of-the-art large-scale global optimization algorithms and conducts a comparative evaluation of their performance on representative test geometries. Analyses of the test results reveal key factors that determine the computational performance of the algorithms from multiple perspectives. These insights further inform the design of advanced evolutionary optimization algorithms for effective tool path planning in five-axis flank milling.
•Conducted a rigorous and comprehensive review of current research in five-axis flank milling tool path planning.•Performed a statistical comparative evaluation of 8 state-of-the-art large-scale optimization algorithms.•Provided in-depth analysis of experimental results to elucidate the underlying mechanisms contributing to performance disparities among the algorithms.