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  2. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    Solution of a travelling salesman problem: the black line shows the shortest possible loop that connects every red dot. In the theory of computational complexity, the travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the ...

  3. Christofides algorithm - Wikipedia

    en.wikipedia.org/wiki/Christofides_algorithm

    There exist inputs to the travelling salesman problem that cause the Christofides algorithm to find a solution whose approximation ratio is arbitrarily close to 3/2. One such class of inputs are formed by a path of n vertices, with the path edges having weight 1, together with a set of edges connecting vertices two steps apart in the path with ...

  4. Concorde TSP Solver - Wikipedia

    en.wikipedia.org/wiki/Concorde_TSP_Solver

    www.math.uwaterloo.ca /tsp /concorde.html 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. 2-opt - Wikipedia

    en.wikipedia.org/wiki/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.

  6. Lin–Kernighan heuristic - Wikipedia

    en.wikipedia.org/wiki/Lin–Kernighan_heuristic

    In combinatorial optimization, Lin–Kernighan is one of the best heuristics for solving the symmetric travelling salesman problem. [citation needed] It belongs to the class of local search algorithms, which take a tour (Hamiltonian cycle) as part of the input and attempt to improve it by searching in the neighbourhood of the given tour for one that is shorter, and upon finding one repeats the ...

  7. Nearest neighbour algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest_neighbour_algorithm

    The nearest neighbour algorithm was one of the first algorithms used to solve the travelling salesman problem approximately. In that problem, the salesman starts at a random city and repeatedly visits the nearest city until all have been visited. The algorithm quickly yields a short tour, but usually not the optimal one.

  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. 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 ...