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  2. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    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.

  3. 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 ]

  4. Maximum coverage problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_coverage_problem

    The greedy algorithm for maximum coverage chooses sets according to one rule: at each stage, choose a set which contains the largest number of uncovered elements. It can be shown that this algorithm achieves an approximation ratio of 1 − 1 e {\displaystyle 1-{\frac {1}{e}}} .

  5. 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.

  6. Metric k-center - Wikipedia

    en.wikipedia.org/wiki/Metric_k-center

    The greedy pure algorithm (or Gr) follows the core idea of greedy algorithms: to take optimal local decisions. In the case of the vertex k-center problem, the optimal local decision consists in selecting each center in such a way that the size of the solution (covering radius) is minimum at each iteration. In other words, the first center ...

  7. Local search (constraint satisfaction) - Wikipedia

    en.wikipedia.org/wiki/Local_search_(constraint...

    The new assignment is close to the previous one in the space of assignment, hence the name local search. All local search algorithms use a function that evaluates the quality of assignment, for example the number of constraints violated by the assignment. This amount is called the cost of the assignment. The aim of local search is that of ...

  8. AOL Mail

    mail.aol.com/?rp=webmail-std/en-us/basic

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. 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.