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  2. Binary space partitioning - Wikipedia

    en.wikipedia.org/wiki/Binary_space_partitioning

    Binary space partitioning arose from computer graphics needing to rapidly draw three-dimensional scenes composed of polygons. A simple way to draw such scenes is the painter's algorithm, which produces polygons in order of distance from the viewer, back to front, painting over the background and previous polygons with each closer object. This ...

  3. Partition problem - Wikipedia

    en.wikipedia.org/wiki/Partition_problem

    The multifit algorithm uses binary search combined with an algorithm for bin packing. In the worst case, its approximation ratio is 8/7. The subset sum problem has an FPTAS which can be used for the partition problem as well, by setting the target sum to sum(S)/2.

  4. Painter's algorithm - Wikipedia

    en.wikipedia.org/wiki/Painter's_algorithm

    A fractal landscape being rendered using the painter's algorithm on an Amiga. The painter's algorithm (also depth-sort algorithm and priority fill) is an algorithm for visible surface determination in 3D computer graphics that works on a polygon-by-polygon basis rather than a pixel-by-pixel, row by row, or area by area basis of other Hidden-Surface Removal algorithms.

  5. Multiway number partitioning - Wikipedia

    en.wikipedia.org/wiki/Multiway_number_partitioning

    The idea is to use binary search to find the optimal makespan. To initialize the binary search, we need a lower bound and an upper bound: Some lower bounds on the makespan are: (sum S)/k - the average value per subset, s 1 - the largest number in S, and s k + s k+1 - the size of a bin in the optimal partition of only the largest k+1 numbers.

  6. Binary search - Wikipedia

    en.wikipedia.org/wiki/Binary_search

    Binary search Visualization of the binary search algorithm where 7 is the target value Class Search algorithm Data structure Array Worst-case performance O (log n) Best-case performance O (1) Average performance O (log n) Worst-case space complexity O (1) Optimal Yes In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search ...

  7. Strong NP-completeness - Wikipedia

    en.wikipedia.org/wiki/Strong_NP-completeness

    An example is the partition problem. Both weak NP-hardness and weak polynomial-time correspond to encoding the input agents in binary coding. If a problem is strongly NP-hard, then it does not even have a pseudo-polynomial time algorithm. It also does not have a fully-polynomial time approximation scheme. An example is the 3-partition problem.

  8. Weak NP-completeness - Wikipedia

    en.wikipedia.org/wiki/Weak_NP-completeness

    An example is the partition problem. Both weak NP-hardness and weak polynomial-time correspond to encoding the input agents in binary coding. If a problem is strongly NP-hard, then it does not even have a pseudo-polynomial time algorithm. It also does not have a fully-polynomial time approximation scheme. An example is the 3-partition problem.

  9. Pseudo-polynomial time - Wikipedia

    en.wikipedia.org/wiki/Pseudo-polynomial_time

    An example is the partition problem. Both weak NP-hardness and weak polynomial-time correspond to encoding the input agents in binary coding. If a problem is strongly NP-hard, then it does not even have a pseudo-polynomial time algorithm. It also does not have a fully-polynomial time approximation scheme. An example is the 3-partition problem.