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In physical simulations, sweep and prune is a broad phase algorithm used during collision detection to limit the number of pairs of solids that need to be checked for collision, i.e. intersection.
Because the feasible space only shrinks as information is added, the objective value for the master function provides a lower bound on the objective function of the overall problem. Benders Decomposition is applicable to problems with a largely block-diagonal structure.
IDA* is a depth-first search that looks for increasingly longer solutions in a series of iterations, using a lower-bound heuristic to prune branches once a lower bound on their length exceeds the current iterations bound. It works roughly as follows. First he identified a number of subproblems that are small enough to be solved optimally. He used:
The lower bound on worst-case running time of output-sensitive convex hull algorithms was established to be Ω(n log h) in the planar case. [1] There are several algorithms which attain this optimal time complexity. The earliest one was introduced by Kirkpatrick and Seidel in 1986 (who called it "the ultimate convex hull algorithm").
The lower bound is weaker than that obtained by stopping the series after the term. A looser version of this bound is that ! + (,] for all . Stirling's formula for ...
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The first function for which superpolynomial circuit lower bounds were shown was the parity function, which computes the sum of its input bits modulo 2. The fact that parity is not contained in AC 0 was first established independently by Ajtai in 1983 [ 3 ] [ 4 ] and by Furst, Saxe and Sipser in 1984. [ 5 ]
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