Search results
Results from the WOW.Com Content Network
The matching pursuit is an example of a greedy algorithm applied on signal approximation. A greedy algorithm finds the optimal solution to Malfatti's problem of finding three disjoint circles within a given triangle that maximize the total area of the circles; it is conjectured that the same greedy algorithm is optimal for any number of circles.
The right example generalises to 2-colorable graphs with n vertices, where the greedy algorithm expends n/2 colors. In the study of graph coloring problems in mathematics and computer science , a greedy coloring or sequential coloring [ 1 ] is a coloring of the vertices of a graph formed by a greedy algorithm that considers the vertices of the ...
Longest-processing-time-first (LPT) is a greedy algorithm for job scheduling. The input to the algorithm is a set of jobs, each of which has a specific processing-time. There is also a number m specifying the number of machines that can process the jobs. The LPT algorithm works as follows:
Kruskal's algorithm [1] finds a minimum spanning forest of an undirected edge-weighted graph.If the graph is connected, it finds a minimum spanning tree.It is a greedy algorithm that in each step adds to the forest the lowest-weight edge that will not form a cycle. [2]
List scheduling is a greedy algorithm for Identical-machines scheduling.The input to this algorithm is a list of jobs that should be executed on a set of m machines. The list is ordered in a fixed order, which can be determined e.g. by the priority of executing the jobs, or by their order of arrival.
In computer science, greedy number partitioning is a class of greedy algorithms for multiway number partitioning. The input to the algorithm is a set S of numbers, and a parameter k. The required output is a partition of S into k subsets, such that the sums in the subsets are as nearly equal as possible. Greedy algorithms process the numbers ...
The Ford–Fulkerson method or Ford–Fulkerson algorithm (FFA) is a greedy algorithm that computes the maximum flow in a flow network.It is sometimes called a "method" instead of an "algorithm" as the approach to finding augmenting paths in a residual graph is not fully specified [1] or it is specified in several implementations with different running times. [2]
The following greedy algorithm finds a solution that contains at least 1/2 of the optimal number of intervals: [8] Select the interval, x, with the earliest finishing time. Remove x, and all intervals intersecting x, and all intervals in the same group of x, from the set of candidate intervals. Continue until the set of candidate intervals is ...