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  2. Admissible heuristic - Wikipedia

    en.wikipedia.org/wiki/Admissible_heuristic

    The search algorithm uses the admissible heuristic to find an estimated optimal path to the goal state from the current node. For example, in A* search the evaluation function (where is the current node) is: = + where = the evaluation function.

  3. Heuristic (computer science) - Wikipedia

    en.wikipedia.org/wiki/Heuristic_(computer_science)

    In mathematical optimization and computer science, heuristic (from Greek εὑρίσκω "I find, discover" [1]) is a technique designed for problem solving more quickly when classic methods are too slow for finding an exact or approximate solution, or when classic methods fail to find any exact solution in a search space.

  4. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    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.

  5. k-medoids - Wikipedia

    en.wikipedia.org/wiki/K-medoids

    The "goodness" of the given value of k can be assessed with methods such as the silhouette method. The medoid of a cluster is defined as the object in the cluster whose sum (and, equivalently, the average) of dissimilarities to all the objects in the cluster is minimal, that is, it is a most centrally located point in the cluster.

  6. List scheduling - Wikipedia

    en.wikipedia.org/wiki/List_scheduling

    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.

  7. Nearest neighbor search - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbor_search

    Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values.

  8. Longest-processing-time-first scheduling - Wikipedia

    en.wikipedia.org/wiki/Longest-processing-time...

    Otherwise, x>5/3. So x was the first input in some greedy bin P m. Let z be the second input added into P m. If x+z≥3, then there are no more inputs in P m, so w(x)=8/3 and we are done. Otherwise, x+z<3. Let v be the smallest input in some greedy bin whose sum exceeds 4. Since x<8/3, z must have been processed before v, so z≥v.

  9. Greedy randomized adaptive search procedure - Wikipedia

    en.wikipedia.org/wiki/Greedy_randomized_adaptive...

    The greedy randomized adaptive search procedure (also known as GRASP) is a metaheuristic algorithm commonly applied to combinatorial optimization problems. GRASP typically consists of iterations made up from successive constructions of a greedy randomized solution and subsequent iterative improvements of it through a local search . [ 1 ]