Algorithmic paradigm (nonfiction): Difference between revisions

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File:Greedy algorithm 36 cents.svg|link=Greedy algorithm (nonfiction)|2018: New study algorithmic paradigms finds that [[Greedy algorithm (nonfiction)|Greedy algorithm]] are studied more often than other algorithmic paradigms.
File:Greedy algorithm 36 cents.svg|link=Greedy algorithm (nonfiction)|September 5, 2018: New study of algorithmic paradigms finds that [[Greedy algorithm (nonfiction)|Greedy algorithms]] are studied more often than other algorithmic paradigms.
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Latest revision as of 10:11, 3 September 2018

An algorithmic paradigm, algorithm design paradigm, algorithmic technique, or algorithmic strategy is a generic method or approach which underlies the design of a class of algorithms.

It is an abstraction higher than the notion of an algorithm, just as an algorithm is an abstraction higher than a computer program.

Examples of algorithmic paradigms include the greedy algorithm in optimization problems, dynamic programming, prune and search, and divide and conquer algorithms. More specialized algorithmic paradigms used in parameterized complexity include kernelization and iterative compression.

In computational geometry, additional algorithmic paradigms include sweep line algorithms, rotating calipers, and randomized incremental construction.

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