Understanding the Empirical Hardness of NP-Complete Problems I
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Understanding the Empirical Hardness of NP-Complete Problems I
Problems are intractable when they “can be solved, but not fast enough for the solution to be usable” [Hopcroft, Motwani
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SOLVED:The complexity of a computer algorithm is the number of operations or steps the algorithm needs to complete its task assuming there are n pieces of input (for example, the number of steps needed to put n numbers in ascending order). Four algorithms for doing the same task have complexities of A: n^3 / 2, B: n log2 n, C: n(log2 n)^2, and D: √(n) log2 n . Rank the algorithms in order of increasing efficiency for large values of n Graph the complexities as they vary with n and comment on you
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