Research on cutting path planning of elastic materials based on improved whale optimization algorithm

Abstract As the demand for elastic materials in critical components such as IC equipment manufacturing, aero-engine blades, and military precision sensors surges, machining complex curved surfaces of elastic materials has met significant technical challenges. Traditional path planning algorithms struggle to balance multiple constraints, including geometric accuracy and material elastic recovery, often resulting in local optimal solutions. To address these issues, this paper constructs a simulation model for the elastic material cutting process and proposes an improved whale optimization algorithm to optimize the cutting path. To enhance the algorithm’s search capabilities and prevent it from getting stuck in local optima, the improved whale algorithm incorporates a nonlinear convergence factor, inertia weight optimization, and a backward whale escape method. Experimental results demonstrate that the improved whale optimization algorithm significantly accelerates convergence, and the optimized cutting path it identifies effectively reduces machining errors caused by elastic recovery.