Genetic Algorithm-Based Design and Path Optimization for Robotic Production Lines

Amid the global trend toward advanced manufacturing, China has actively enforced energy conservation and carbon reduction policies, imposing stricter requirements on energy consumption and production cycles in robotic assembly lines. Taking the automotive lamp assembly line of a specific enterprise as a case study, this work develops a mathematical model and applies an enhanced genetic algorithm to optimize the mobile trajectories of industrial robots. The optimized system reduces the production cycle by 10% while minimizing energy consumption. This method facilitates the precise configuration of key parameters during the design stage, significantly shortens the commissioning period, and notably improves production efficiency. The proposed approach demonstrates strong practical applicability and broad market potential, underscoring the intelligent and sustainable evolution of future manufacturing systems.