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What is the space complexity of Travelling salesman problem?
A New Exact Algorithm for Traveling Salesman Problem with Time Complexity Interval (O(n^4), O(n^3*2^n)) Traveling salesman problem is a NP-hard problem.
Can we solve Travelling salesman problem using backtracking?
Travelling Salesman Problem (TSP): Given a set of cities and distance between every pair of cities, the problem is to find the shortest possible route that visits every city exactly once and returns back to the starting point.
How are the shortest path and traveling salesman problem given above similar?
They are similar, because each of then has to walk a graph and find a path in them. The difference is the constraint on the solution. The shortest-path requires just a path between two points, while the traveling salesman requires a path between more points that returns to the first point.
Is the traveling salesman problem a combinatorial problem?
The traveling salesman problem is a classic problem in combinatorial optimization. This problem is to find the shortest path that a salesman should take to traverse through a list of cities and return to the origin city. The list of cities and the distance between each pair are provided.
How to solve the traveling salesman problem or TSP?
You can solve the traveling salesman problem or TSP with dynamic programming, simulated annealing, and 2-opt methods. My suggestion is the 2-opt method.
How to solve the traveling salesman problem in artificial intelligence?
Artificial Intelligence: Unorthodox Lessons: How to Gain Insight and Build Innovative Solutions: Ataee, Pedram… The traveling salesman problem is a classic problem in combinatorial optimization. This problem is to find the shortest path that a salesman should take to traverse through a list of cities and return to the origin city.
Is the problem of finding the shortest salesman tour NPO-complete?
In the general case, finding a shortest travelling salesman tour is NPO-complete. If the distance measure is a metric (and thus symmetric), the problem becomes APX-complete and Christofides’s algorithm approximates it within 1.5.