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  2. Travelling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Travelling_salesman_problem

    One of the earliest applications of dynamic programming is the Held–Karp algorithm, which solves the problem in time (). [24] This bound has also been reached by Exclusion-Inclusion in an attempt preceding the dynamic programming approach. Solution to a symmetric TSP with 7 cities using brute force search.

  3. 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 ...

  4. Concorde TSP Solver - Wikipedia

    en.wikipedia.org/wiki/Concorde_TSP_Solver

    According to Mulder & Wunsch (2003), Concorde “is widely regarded as the fastest TSP solver, for large instances, currently in existence.” In 2001, Concorde won a 5000 guilder prize from CMG for solving a vehicle routing problem the company had posed in 1996. [7] Concorde requires a linear programming solver and only supports QSopt [8] and ...

  5. LeetCode - Wikipedia

    en.wikipedia.org/wiki/LeetCode

    LeetCode LLC, doing business as LeetCode, is an online platform for coding interview preparation. The platform provides coding and algorithmic problems intended for users to practice coding . [ 1 ] LeetCode has gained popularity among job seekers in the software industry and coding enthusiasts as a resource for technical interviews and coding ...

  6. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    If the solution to any problem can be formulated recursively using the solution to its sub-problems, and if its sub-problems are overlapping, then one can easily memoize or store the solutions to the sub-problems in a table (often an array or hashtable in practice). Whenever we attempt to solve a new sub-problem, we first check the table to see ...

  7. Christofides algorithm - Wikipedia

    en.wikipedia.org/wiki/Christofides_algorithm

    The cost of the solution produced by the algorithm is within 3/2 of the optimum. To prove this, let C be the optimal traveling salesman tour. Removing an edge from C produces a spanning tree, which must have weight at least that of the minimum spanning tree, implying that w(T) ≤ w(C) - lower bound to the cost of the optimal solution.

  8. Bottleneck traveling salesman problem - Wikipedia

    en.wikipedia.org/wiki/Bottleneck_traveling...

    In an asymmetric bottleneck TSP, there are cases where the weight from node A to B is different from the weight from B to A (e. g. travel time between two cities with a traffic jam in one direction). The Euclidean bottleneck TSP, or planar bottleneck TSP, is the bottleneck TSP with the distance being the ordinary Euclidean distance. The problem ...

  9. Set TSP problem - Wikipedia

    en.wikipedia.org/wiki/Set_TSP_problem

    In combinatorial optimization, the set TSP, also known as the generalized TSP, group TSP, One-of-a-Set TSP, Multiple Choice TSP or Covering Salesman Problem, is a generalization of the traveling salesman problem (TSP), whereby it is required to find a shortest tour in a graph which visits all specified subsets of the vertices of a graph.