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  2. Greedy number partitioning - Wikipedia

    en.wikipedia.org/wiki/Greedy_number_partitioning

    Several additional heuristics can be used to improve the runtime: [2] In a node in which the current sum-difference is at least the sum of all remaining numbers, the remaining numbers can just be put in the smallest-sum subset. If we reach a leaf in which the sum-difference is 0 or 1, then the algorithm can terminate since this is the optimum.

  3. Multiway number partitioning - Wikipedia

    en.wikipedia.org/wiki/Multiway_number_partitioning

    [2] Minimize the largest sum. This objective is equivalent to one objective for Identical-machines scheduling. There are k identical processors, and each number in S represents the time required to complete a single-processor job. The goal is to partition the jobs among the processors such that the makespan (the finish time of the last job) is ...

  4. Largest differencing method - Wikipedia

    en.wikipedia.org/wiki/Largest_differencing_method

    LDM always returns a partition in which the largest sum is at most 7/6 times the optimum. [4] This is tight when there are 5 or more items. [2] On random instances, this approximate algorithm performs much better than greedy number partitioning. However, it is still bad for instances where the numbers are exponential in the size of the set. [5]

  5. Balanced number partitioning - Wikipedia

    en.wikipedia.org/wiki/Balanced_number_partitioning

    The two subsets should contain floor(n/2) and ceiling(n/2) items. It is a variant of the partition problem. It is NP-hard to decide whether there exists a partition in which the sums in the two subsets are equal; see [4] problem [SP12]. There are many algorithms that aim to find a balanced partition in which the sum is as nearly-equal as possible.

  6. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    Given the two sorted lists, the algorithm can check if an element of the first array and an element of the second array sum up to T in time (/). To do that, the algorithm passes through the first array in decreasing order (starting at the largest element) and the second array in increasing order (starting at the smallest element).

  7. Partition problem - Wikipedia

    en.wikipedia.org/wiki/Partition_problem

    In number theory and computer science, the partition problem, or number partitioning, [1] is the task of deciding whether a given multiset S of positive integers can be partitioned into two subsets S 1 and S 2 such that the sum of the numbers in S 1 equals the sum of the numbers in S 2. Although the partition problem is NP-complete, there is a ...

  8. Multiple subset sum - Wikipedia

    en.wikipedia.org/wiki/Multiple_subset_sum

    The multiple subset sum problem is an optimization problem in computer science and operations research.It is a generalization of the subset sum problem.The input to the problem is a multiset of n integers and a positive integer m representing the number of subsets.

  9. Partition function (number theory) - Wikipedia

    en.wikipedia.org/wiki/Partition_function_(number...

    The values (), …, of the partition function (1, 2, 3, 5, 7, 11, 15, and 22) can be determined by counting the Young diagrams for the partitions of the numbers from 1 to 8. In number theory, the partition function p(n) represents the number of possible partitions of a non-negative integer n.