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  2. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    Greedy algorithms fail to produce the optimal solution for many other problems and may even produce the unique worst possible solution. One example is the travelling salesman problem mentioned above: for each number of cities, there is an assignment of distances between the cities for which the nearest-neighbour heuristic produces the unique ...

  3. Set cover problem - Wikipedia

    en.wikipedia.org/wiki/Set_cover_problem

    This greedy algorithm actually achieves an approximation ratio of (′) where ′ is the maximum cardinality set of . For δ − {\displaystyle \delta -} dense instances, however, there exists a c ln ⁡ m {\displaystyle c\ln {m}} -approximation algorithm for every c > 0 {\displaystyle c>0} .

  4. Assignment problem - Wikipedia

    en.wikipedia.org/wiki/Assignment_problem

    This algorithm may yield a non-optimal solution. For example, suppose there are two tasks and two agents with costs as follows: Alice: Task 1 = 1, Task 2 = 2. George: Task 1 = 5, Task 2 = 8. The greedy algorithm would assign Task 1 to Alice and Task 2 to George, for a total cost of 9; but the reverse assignment has a total cost of 7.

  5. Greedy number partitioning - Wikipedia

    en.wikipedia.org/wiki/Greedy_number_partitioning

    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 ...

  6. Maximum coverage problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_coverage_problem

    First, find a solution using greedy algorithm. In each iteration of the greedy algorithm the tentative solution is added the set which contains the maximum residual weight of elements divided by the residual cost of these elements along with the residual cost of the set. Second, compare the solution gained by the first step to the best solution ...

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

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

    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:

  8. Partition problem - Wikipedia

    en.wikipedia.org/wiki/Partition_problem

    Algorithms developed for multiway number partitioning include: The pseudopolynomial time number partitioning takes () memory, where m is the largest number in the input. The Complete Greedy Algorithm (CGA) considers all partitions by constructing a binary tree. Each level in the tree corresponds to an input number, where the root corresponds to ...

  9. Optimal substructure - Wikipedia

    en.wikipedia.org/wiki/Optimal_substructure

    This property is used to determine the usefulness of greedy algorithms for a problem. [1] Typically, a greedy algorithm is used to solve a problem with optimal substructure if it can be proven by induction that this is optimal at each step. [1] Otherwise, provided the problem exhibits overlapping subproblems as well, divide-and-conquer methods ...