Local search algorithms are optimization techniques used to solve combinatorial problems by exploring the solution space iteratively and making incremental changes to a current solution. They are particularly useful in approximation algorithms, as they help find near-optimal solutions by navigating through neighborhoods of potential solutions rather than exhaustively searching the entire space. This approach is beneficial in cases where finding the exact solution is computationally expensive or infeasible.
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