Local search is an optimization algorithm used in AI and computer science to find the optimal solution by iteratively improving the current solution. Local search is used for problems where finding the global optimal solution is infeasible, and the focus is on finding a solution that is "good enough".
- Initialize the search with a random or initial solution
- Generate a set of neighboring solutions
- Evaluate the quality of each neighboring solution
- Choose the best neighboring solution as the new current solution
- Repeat steps 2-4 until the stopping condition is met
Local search is a fast and efficient algorithm for finding a "good enough" solution for optimization problems. However, it can get stuck in local optima, and it does not guarantee finding the global optimal solution. Therefore, it is often used in combination with other optimization algorithms to improve its performance.