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Greedy algorithms determine the minimum number of coins to give while making change. These are the steps most people would take to emulate a greedy algorithm to represent 36 cents using only coins with values {1, 5, 10, 20}. The coin of the highest value, less than the remaining change owed, is the local optimum.
In mathematics, the greedy algorithm for Egyptian fractions is a greedy algorithm, first described by Fibonacci, for transforming rational numbers into Egyptian fractions. An Egyptian fraction is a representation of an irreducible fraction as a sum of distinct unit fractions , such as 5 / 6 = 1 / 2 + 1 / 3 .
One variation of this problem assumes that the people making change will use the "greedy algorithm" for making change, even when that requires more than the minimum number of coins. Most current currencies use a 1-2-5 series , but some other set of denominations would require fewer denominations of coins or a smaller average number of coins to ...
The natural generalization of the greedy number partitioning algorithm is the envy-graph algorithm. It guarantees that the allocation is envy-free up to at most one item (EF1). Moreover, if the instance is ordered (- all agents rank the items in the same order), then the outcome is EFX, and guarantees to each agent at least 2 n 3 n − 1 ...
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These algorithms typically do not work well for larger read sets, as they do not easily reach a global optimum in the assembly, and do not perform well on read sets that contain repeat regions. [1] Early de novo sequence assemblers, such as SEQAID [2] (1984) and CAP [3] (1992), used greedy algorithms, such as overlap-layout-consensus (OLC ...
It is known [20] that every x / y with odd y has an expansion into distinct odd unit fractions, constructed using a different method than the greedy algorithm. It is possible to use brute-force search algorithms to find the Egyptian fraction representation of a given number with the fewest possible terms [ 21 ] or minimizing the largest ...
The package-merge algorithm is an O(nL)-time algorithm for finding an optimal length-limited Huffman code for a given distribution on a given alphabet of size n, where no code word is longer than L. It is a greedy algorithm , and a generalization of Huffman's original algorithm .