Solving the NP-Completeness of Travelling Salesman Problem

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Discussion Overview

The discussion revolves around the classification of the Travelling Salesman Problem (TSP) in terms of computational complexity, specifically addressing whether it is NP-complete or NP-hard. Participants explore the implications of different formulations of the problem, including the decision version and the verification of routes.

Discussion Character

  • Debate/contested, Technical explanation

Main Points Raised

  • One participant expresses confusion about how the TSP can be NP-complete, particularly questioning the polynomial-time verification of the shortest route.
  • Another participant asserts that TSP is NP-hard, clarifying that the decision version of the problem, which asks if there is a path shorter than a given length, is NP-complete.
  • A third participant notes that TSP is considered NP-complete only when referring to its decision version.
  • A side note mentions a personal interest in combinatorial optimization as a related topic.

Areas of Agreement / Disagreement

Participants exhibit disagreement regarding the classification of TSP, with some asserting it is NP-hard while others maintain it is NP-complete in the context of the decision version. The discussion remains unresolved as differing views are presented.

Contextual Notes

The discussion highlights the distinction between NP-completeness and NP-hardness, but does not resolve the implications of these classifications or the specifics of polynomial-time verification.

Dragonfall
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I don't understand how travenlling salesman is NP-complete. In particular, how can you possibly verify that a given route is the shortest one in polynomial time?
 
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The TSP isn't NP-complete - it's NP-hard. But the question: Is there a path shorter than x is NP-complete. A problem is NP-hard iff it can be used to solve an NP-complete problem in O(n) time.
 
Last edited:
TSP is only NP-complete if you use the decision version of the problem.

Side note, TSP is one reason why combinatorial optimization is one of my favorite subjects.
 
This makes a lot more sense.
 

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