enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    By the triangle inequality, the best Eulerian graph must have the same cost as the best travelling salesman tour; hence, finding optimal Eulerian graphs is at least as hard as TSP. One way of doing this is by minimum weight matching using algorithms with a complexity of O ( n 3 ) {\displaystyle O(n^{3})} .

  3. Christofides algorithm - Wikipedia

    en.wikipedia.org/wiki/Christofides_algorithm

    This algorithm is no longer the best polynomial time approximation algorithm for the TSP on general metric spaces. Karlin, Klein, and Gharan introduced a randomized approximation algorithm with approximation ratio 1.5 − 10 −36. It follows similar principles to Christofides' algorithm, but uses a randomly chosen tree from a carefully chosen ...

  4. Concorde TSP Solver - Wikipedia

    en.wikipedia.org/wiki/Concorde_TSP_Solver

    The Concorde TSP Solver is a program for solving the travelling salesman problem. It was written by David Applegate , Robert E. Bixby , Vašek Chvátal , and William J. Cook , in ANSI C , and is freely available for academic use.

  5. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    In the worst case, the algorithm results in a tour that is much longer than the optimal tour. To be precise, for every constant r there is an instance of the traveling salesman problem such that the length of the tour computed by the nearest neighbour algorithm is greater than r times the length of the optimal tour. Moreover, for each number of ...

  6. Held–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Held–Karp_algorithm

    The Held–Karp algorithm, also called the Bellman–Held–Karp algorithm, is a dynamic programming algorithm proposed in 1962 independently by Bellman [1] and by Held and Karp [2] to solve the traveling salesman problem (TSP), in which the input is a distance matrix between a set of cities, and the goal is to find a minimum-length tour that visits each city exactly once before returning to ...

  7. 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]

  8. Multi-fragment algorithm - Wikipedia

    en.wikipedia.org/wiki/Multi-fragment_algorithm

    The algorithm builds a tour for the traveling salesman one edge at a time and thus maintains multiple tour fragments, each of which is a simple path in the complete graph of cities. At each stage, the algorithm selects the edge of minimal cost that either creates a new fragment, extends one of the existing paths or creates a cycle of length ...

  9. 3-opt - Wikipedia

    en.wikipedia.org/wiki/3-opt

    In optimization, 3-opt is a simple local search heuristic for finding approximate solutions to the travelling salesperson problem and related network optimization problems. . Compared to the simpler 2-opt algorithm, it is slower but can generate higher-quality soluti