MULTI-OBJECTIVE OPTIMIZATION OF HIGH-SPEED TRAIN INTEGRATED GROUNDING SYSTEMS USING NSGA-II

This study develops a multi-objective optimization framework for high-speed train integrated grounding systems, addressing the conflicting goals of minimizing train body (TB) current and transient overvoltage. Using a validated catenary–train–rail coupling model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the study identifies Pareto-optimal grounding configurations that reduce TB current and overvoltage by up to 70% and 39%, respectively. The proposed framework eliminates manual tuning limitations and provides a systematic design tool for safer and more efficient grounding systems.