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Local search is applied when you want to efficiently find a solution to a problem in a large space of candidate solutions, and the path to the solution or goal state is irrelevant. It operates using a single current node and moving to neighbors of that node. Good for solving optimization problems in which the aim is to find the best state according to an objective function.
SEE ALSO:  Goal State, Search, State
Applications:  desktopGA
LOCAL SEARCH (OPERATOR)
Local search can be applied as an operator to individuals in each iteration of an evolutionary algorithm. It is used to refine solutions in their local neighborhood and more efficient when applied infrequently. First-choice hill climbing is the preferred strategy as it is faster than plain hill climbing.