IALA-BPNN-MOEDO

This codebase implements a complete multi-objective optimization framework for robotic arm structural design, comprising three core modules: ALA (metaheuristic algorithm comparison and ablation studies), BPNN (neural network surrogate model training), and MOPSO (MOEDO-based multi-objective optimizer). The framework generates training data via finite element analysis, optimizes BPNN parameters using an improved artificial lemming algorithm(IALA), and ultimately achieves Pareto-optimal designs for geometric parameters (mass, stress, deformation). Suitable for structural optimization, algorithmic research, and engineering applications.