Does the TSP (traveling salesman problem) change in difficulty when the number of dimensions is greater than...











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The title pretty much says it all.



I am curious if the TSP is dependent only upon the number of cities, $c$, involved, or if the dimensionality, $d$, matters to the problem.



For example, if $d>>c$ does the problem shift in some manner, making the time to solve the problem less dependent on the number of cities?










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    up vote
    1
    down vote

    favorite












    The title pretty much says it all.



    I am curious if the TSP is dependent only upon the number of cities, $c$, involved, or if the dimensionality, $d$, matters to the problem.



    For example, if $d>>c$ does the problem shift in some manner, making the time to solve the problem less dependent on the number of cities?










    share|cite|improve this question
























      up vote
      1
      down vote

      favorite









      up vote
      1
      down vote

      favorite











      The title pretty much says it all.



      I am curious if the TSP is dependent only upon the number of cities, $c$, involved, or if the dimensionality, $d$, matters to the problem.



      For example, if $d>>c$ does the problem shift in some manner, making the time to solve the problem less dependent on the number of cities?










      share|cite|improve this question













      The title pretty much says it all.



      I am curious if the TSP is dependent only upon the number of cities, $c$, involved, or if the dimensionality, $d$, matters to the problem.



      For example, if $d>>c$ does the problem shift in some manner, making the time to solve the problem less dependent on the number of cities?







      graph-theory algorithms






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      share|cite|improve this question











      share|cite|improve this question




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      asked Dec 1 at 19:59









      chase

      1326




      1326






















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          The traveling salesman problem is, in its basic form, a graph theory problem. All vertices (the cities to visit) are connected, and all edges are assigned a "distance", and you need to answer: "what is the shortest route that starts at a given vertex, visits all other vertices, and comes back to the start point?"



          The only thing that changes in a multi-dimensional format is that calculating these distances takes more variables, but this is calculated in linear time (I'm assuming Euclidean distances). But once you get calculate them all and get the graph described above, the problem is exactly the same. So no change in complexity.






          share|cite|improve this answer

















          • 2




            Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
            – Ian
            Dec 1 at 20:45








          • 1




            What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
            – Misha Lavrov
            Dec 1 at 22:29






          • 1




            Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
            – David C. Ullrich
            Dec 2 at 18:49











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          1 Answer
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          active

          oldest

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          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes








          up vote
          4
          down vote



          accepted










          The traveling salesman problem is, in its basic form, a graph theory problem. All vertices (the cities to visit) are connected, and all edges are assigned a "distance", and you need to answer: "what is the shortest route that starts at a given vertex, visits all other vertices, and comes back to the start point?"



          The only thing that changes in a multi-dimensional format is that calculating these distances takes more variables, but this is calculated in linear time (I'm assuming Euclidean distances). But once you get calculate them all and get the graph described above, the problem is exactly the same. So no change in complexity.






          share|cite|improve this answer

















          • 2




            Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
            – Ian
            Dec 1 at 20:45








          • 1




            What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
            – Misha Lavrov
            Dec 1 at 22:29






          • 1




            Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
            – David C. Ullrich
            Dec 2 at 18:49















          up vote
          4
          down vote



          accepted










          The traveling salesman problem is, in its basic form, a graph theory problem. All vertices (the cities to visit) are connected, and all edges are assigned a "distance", and you need to answer: "what is the shortest route that starts at a given vertex, visits all other vertices, and comes back to the start point?"



          The only thing that changes in a multi-dimensional format is that calculating these distances takes more variables, but this is calculated in linear time (I'm assuming Euclidean distances). But once you get calculate them all and get the graph described above, the problem is exactly the same. So no change in complexity.






          share|cite|improve this answer

















          • 2




            Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
            – Ian
            Dec 1 at 20:45








          • 1




            What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
            – Misha Lavrov
            Dec 1 at 22:29






          • 1




            Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
            – David C. Ullrich
            Dec 2 at 18:49













          up vote
          4
          down vote



          accepted







          up vote
          4
          down vote



          accepted






          The traveling salesman problem is, in its basic form, a graph theory problem. All vertices (the cities to visit) are connected, and all edges are assigned a "distance", and you need to answer: "what is the shortest route that starts at a given vertex, visits all other vertices, and comes back to the start point?"



          The only thing that changes in a multi-dimensional format is that calculating these distances takes more variables, but this is calculated in linear time (I'm assuming Euclidean distances). But once you get calculate them all and get the graph described above, the problem is exactly the same. So no change in complexity.






          share|cite|improve this answer












          The traveling salesman problem is, in its basic form, a graph theory problem. All vertices (the cities to visit) are connected, and all edges are assigned a "distance", and you need to answer: "what is the shortest route that starts at a given vertex, visits all other vertices, and comes back to the start point?"



          The only thing that changes in a multi-dimensional format is that calculating these distances takes more variables, but this is calculated in linear time (I'm assuming Euclidean distances). But once you get calculate them all and get the graph described above, the problem is exactly the same. So no change in complexity.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Dec 1 at 20:13









          Jeffery

          834




          834








          • 2




            Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
            – Ian
            Dec 1 at 20:45








          • 1




            What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
            – Misha Lavrov
            Dec 1 at 22:29






          • 1




            Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
            – David C. Ullrich
            Dec 2 at 18:49














          • 2




            Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
            – Ian
            Dec 1 at 20:45








          • 1




            What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
            – Misha Lavrov
            Dec 1 at 22:29






          • 1




            Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
            – David C. Ullrich
            Dec 2 at 18:49








          2




          2




          Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
          – Ian
          Dec 1 at 20:45






          Graph theory does have a notion of dimensionality to it, in that a graph may or may not be embeddable into $mathbb{R}^n$ for certain $n$ (where "embedabble" means it can be drawn without intersecting edges). The smallest $n$ for which this can be done can be interpreted as the dimension of the graph itself. This dimensionality enters into certain problems (for example, coloring problems). It doesn't really enter into the TSP in any significant way, however.
          – Ian
          Dec 1 at 20:45






          1




          1




          What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
          – Misha Lavrov
          Dec 1 at 22:29




          What does affect TSP is whether the edge costs are metric: whether they satisfy the triangle inequality $d(u,w) le d(u,v) + d(v,w)$. If the graph is embeddable in $mathbb R^n$ for any $n$, then the edge costs (Euclidean distances) are metric, which allows for some approximation algorithms that do not work in general.
          – Misha Lavrov
          Dec 1 at 22:29




          1




          1




          Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
          – David C. Ullrich
          Dec 2 at 18:49




          Except of course for $d=1$: If the cities are points of $Bbb R$ with the euclidean distance then the TSP is pretty easy...
          – David C. Ullrich
          Dec 2 at 18:49


















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