Optimizing Task Allocation in the LHC Computing Grid for the High-Luminosity LHC Using a Heuristic Approach.

This is version v2.0.1 of the study on optimizing task allocation in the LHC Computing Grid for the High-Luminosity LHC. Improvements include: - **Algorithm Optimization**: Tuned Simulated Annealing parameters (dynamic T_0 = 1000 * sqrt(N*M/25000), alpha = 0.9, max_iter = 500) for a 10-20% reduction in runtime (e.g., from 60s to 51s for N=170, M=5000).- **Extended Scenario**: Added a new scenario with N=100 (50 CPU EPYC 9005, 50 GPU NVIDIA H100) and M=1000, achieving up to 40% energy savings (estimated 3700 kWh vs. 5814 kWh).- **Enhanced Visualization**: Updated optimization_chart.png to optimization_chart_v2.png with dual Y-axes (Energy/Cost on left, Time/GPU Tasks on right) for better clarity across scenarios.- **Documentation**: Updated main.tex with a comparative table (N=50, N=100), a Data Availability section, and corrected encoding issues (e.g., "CERN’s" to "CERN's"). Code and data are available in the GitHub repository https://github.com/DonMask/LHC-Computing-Grid