Local search algorithms work by maintaining a single “current state” or a small set of states and trying to improve them iteratively. The best advantage of local searching is that we can control the amount of memory we use; therefore, this is a very efficient strategy in terms of memory. In computer science, local search is a heuristic method for solving computationally complex optimization problems. The local search can be used in problems that can be formulated such as the search for a solution that maximizes a criterion among a series of candidate solutions.
Local search algorithms move from one solution to another in the candidate solution space (the search space) by applying local changes, until a solution that is considered optimal is found or a deadline has elapsed. Local search applies directly to optimization problems, where local search is used to minimize the objective function, rather than to find a solution.