In order to analyze the impact of different heuristic methods on the precision of microseismic source localization, an optimized Dominant Wolf Pack Algorithm(DWPA)is proposed.This algorithm builds upon the Dominant Wolf Pack Algorithm and introduces adjustments to two parameters, namely the search step size and the siege step size, enhancing its ability to escape local optima during the search process.The effectiveness of the optimized DWPA is validated through theoretical model inversion and engineering numerical analysis.A comparative study with commonly used heuristic algorithms, Particle Swarm Optimization(PSO)and Simulated Annealing(SA), reveals that the optimized DWPA exhibits faster convergence, higher accuracy, and reduced sensitivity to P-wave velocity errors.This research provides new insights for the application of intelligent heuristic algorithms in microseismic source localization.
