Performance Comparison of A* Search Algorithm and Hill-Climb Search Algorithm: A Case Study
Raghvendra Kumar, Goggi Ruthvik Tarang, Kashyap Koutilya Adipudi, Vasista Parvathaneni, Gopaldas Steven · 2024
A comparative analysis of the performance of A* and Hill-Climb search algorithms in solving optimization problems is presented. A* uses an admissible heuristic function to guide the search to promising paths, taking into account the cost of reaching a state, while Hill-Climb search explores neighboring states approach, move to the state with the highest function value goal. The study evaluates the performance in terms of solution quality, execution time, and search complexity in different problem cases. The results show that A* search often outperforms Hill-Climb search in complex state space and multi- objective optimization, while Hill-Climb search exhibits fast convergence and efficiency than in a simpler state space. The choice of heuristic functions, the characteristics of the problem, and the complexity of the search space affect the performance of both algorithms. This analysis provides valuable information for selecting the appropriate search algorithm based on specific requirements of the problem.