Robust Project Scheduling Optimization for Extra-long Railway Tunnel Engineering Considering Resource Transfer

To ensure reliable execution of construction schedules and maintain low costs for extra-long railway tunnel engineering under uncertainty, a robust project scheduling optimization model is established with objectives of maximizing schedule robustness and minimizing total cost under deadline constraints. The model incorporates the impact of resource transfer on time buffers and introduces a time buffer calculation method for start-to-start precedence relationships considering rock grade variations. A TS-NSGA-Ⅱ algorithm tailored to model characteristics is designed, employing NSGA-Ⅱ with adaptive genetic operations as the main framework, and integrating a tabu search-based elite strategy for generating neighborhood solutions to enhance both global and local search capabilities. Simulation results demonstrate that the proposed model and algorithm can effectively generate scheduling plans with reliable execution and low construction costs, yielding an 11.33% improvement in robustness over the model without resource transfer. Comparative case studies show that TS-NSGA-Ⅱ achieves superior solution quality and computational efficiency, and can satisfy the scheduling optimization requirements of extra-long railway tunnel engineering under uncertainty.