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  2. 2-opt - Wikipedia

    en.wikipedia.org/wiki/2-opt

    2-opt. In optimization, 2-opt is a simple local search algorithm for solving the traveling salesman problem. The 2-opt algorithm was first proposed by Croes in 1958, [ 1 ] although the basic move had already been suggested by Flood. [ 2 ] The main idea behind it is to take a route that crosses over itself and reorder it so that it does not.

  3. Branch and bound - Wikipedia

    en.wikipedia.org/wiki/Branch_and_bound

    Branch and bound. Branch and bound (BB, B&B, or BnB) is a method for solving optimization problems by breaking them down into smaller sub-problems and using a bounding function to eliminate sub-problems that cannot contain the optimal solution. It is an algorithm design paradigm for discrete and combinatorial optimization problems, as well as ...

  4. Longest common subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_common_subsequence

    A longest common subsequence (LCS) is the longest subsequence common to all sequences in a set of sequences (often just two sequences). It differs from the longest common substring: unlike substrings, subsequences are not required to occupy consecutive positions within the original sequences. The problem of computing longest common subsequences ...

  5. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    Travelling Salesman, by director Timothy Lanzone, is the story of four mathematicians hired by the U.S. government to solve the most elusive problem in computer-science history: P vs. NP. [ 77 ] Solutions to the problem are used by mathematician Robert A. Bosch in a subgenre called TSP art.

  6. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10]. In computer science, the maximum sum subarray problem, also known as the maximum segment sum problem, is the task of finding a contiguous subarray with the largest sum, within a given one-dimensional array A [1...n] of numbers. It can be solved in time and space.

  7. Flood fill - Wikipedia

    en.wikipedia.org/wiki/Flood_fill

    Flood fill, also called seed fill, is a flooding algorithm that determines and alters the area connected to a given node in a multi-dimensional array with some matching attribute. It is used in the "bucket" fill tool of paint programs to fill connected, similarly-colored areas with a different color, and in games such as Go and Minesweeper for ...

  8. Pseudocode - Wikipedia

    en.wikipedia.org/wiki/Pseudocode

    Pseudocode. In computer science, pseudocode is a description of the steps in an algorithm using a mix of conventions of programming languages (like assignment operator, conditional operator, loop) with informal, usually self-explanatory, notation of actions and conditions. [ 1 ][ 2 ] Although pseudocode shares features with regular programming ...

  9. Longest increasing subsequence - Wikipedia

    en.wikipedia.org/wiki/Longest_increasing_subsequence

    one of the longest increasing subsequences is. 0, 2, 6, 9, 11, 15. This subsequence has length six; the input sequence has no seven-member increasing subsequences. The longest increasing subsequence in this example is not the only solution: for instance, are other increasing subsequences of equal length in the same input sequence.