Local Search (optimization)
In computer science, local search is a metaheuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution maximizing a criterion among a number of candidate solutions. Local search algorithms move from solution to solution in the space of candidate solutions (the search space) by applying local changes, until a solution deemed optimal is found or a time bound is elapsed.
Local search algorithms are widely applied to numerous hard computational problems, including problems from computer science (particularly artificial intelligence), mathematics, operations research, engineering, and bioinformatics. Examples of local search algorithms are WalkSAT and the 2-opt algorithm for the Traveling Salesman Problem.
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Famous quotes containing the words local and/or search:
“The local is a shabby thing. There’s nothing worse than bringing us back down to our own little corner, our own territory, the radiant promiscuity of the face to face. A culture which has taken the risk of the universal, must perish by the universal.”
—Jean Baudrillard (b. 1929)
“The danger lies in forgetting what we had. The flow between generations becomes a trickle, grandchildren tape-recording grandparents’ memories on special occasions perhaps—no casual storytelling jogged by daily life, there being no shared daily life what with migrations, exiles, diasporas, rendings, the search for work. Or there is a shared daily life riddled with holes of silence.”
—Adrienne Rich (b. 1929)