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  2. Multiway number partitioning - Wikipedia

    en.wikipedia.org/wiki/Multiway_number_partitioning

    Let C i (for i between 1 and k) be the sum of subset i in a given partition. Instead of minimizing the objective function max(C i), one can minimize the objective function max(f(C i)), where f is any fixed function. Similarly, one can minimize the objective function sum(f(C i)), or maximize min(f(C i)), or maximize sum(f(C i)).

  3. Greedy number partitioning - Wikipedia

    en.wikipedia.org/wiki/Greedy_number_partitioning

    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 sequentially, and insert the next number into a bin in which the sum of numbers is currently smallest.

  4. 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 S {\displaystyle S} of n integers and a positive integer m representing the number of subsets.

  5. Partition problem - Wikipedia

    en.wikipedia.org/wiki/Partition_problem

    In the subset sum problem, the goal is to find a subset of S whose sum is a certain target number T given as input (the partition problem is the special case in which T is half the sum of S). In multiway number partitioning , there is an integer parameter k , and the goal is to decide whether S can be partitioned into k subsets of equal sum ...

  6. Balanced number partitioning - Wikipedia

    en.wikipedia.org/wiki/Balanced_number_partitioning

    Balanced number partitioning is a variant of multiway number partitioning in which there are constraints on the number of items allocated to each set. The input to the problem is a set of n items of different sizes, and two integers m, k.

  7. Subset sum problem - Wikipedia

    en.wikipedia.org/wiki/Subset_sum_problem

    Let A be the sum of the negative values and B the sum of the positive values; the number of different possible sums is at most B-A, so the total runtime is in (()). For example, if all input values are positive and bounded by some constant C , then B is at most N C , so the time required is O ( N 2 C ) {\displaystyle O(N^{2}C)} .

  8. Partition (database) - Wikipedia

    en.wikipedia.org/wiki/Partition_(database)

    Partitioning is commonly implemented alongside replication, storing partition copies across multiple nodes. Each record belongs to one partition but may exist on multiple nodes for fault tolerance. In leader-follower replication systems, nodes can simultaneously serve as leaders for some partitions and followers for others. [1]

  9. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]