Optimal TSP-Tour in Grid-City: Let's Find Out

  • MHB
  • Thread starter mathmari
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In summary, we discussed the TSP problem in Grid-City, where the roads form a grid and the distance between two points is defined as the sum of their horizontal and vertical distances. We were given an input of 203 points with coordinates, and we aimed to find the optimal TSP tour. We considered starting from (0,0) and found the second point to be (1,0) based on the distances. From there, we discussed the possibility of using diagonal lines and whether they would affect the optimal tour. We also explored the use of NEAREST-NEIGHBOR and NEAREST-INSERTION algorithms to approximate the optimal tour.
  • #1
mathmari
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MHB
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Hey! :eek:

We consider the TSP in Grid-City.
The roads in Grid-City have the form of a grid, so that the intersection points can be described by an integer coordinate system.
The distance of $2$ points $C=(x,y)$ and $D=(x',y')$ is defined as $d(C,D)=|x-x'|+|y-y'|$.
An input for the TSP consists of $203$ points with the following coordinates:
$$(i,0), \text{ for } i=0, 1, \dots , 100, \\ (i,2), \text{ for } i=0, 1, \dots , 100, \\ (103, 0)$$
I want to give the optimal TSP-Tour. We have the following grid, or not?
View attachment 5787
(Wondering)

To find the optimal TSP-Tour from which point do we start? From which point we want? (Wondering)
If we choose one point to start, let's consider the $S=(0,0)$.
The second point will be either $A=(0,2)$ or $B=(1,0)$, right? Since $2=d(S,A)>d(S,B)=1$, the second point is $B=(1,0)$.
Or can we consider for the second point also the diagonal one, $(1,2)$ ? (Wondering)
Or is this not the correct way to find the optimal TSP-Tour? (Wondering)

When the roads are just the vertical and horizontal lines, we have that the distance of a point $(i,j)$ to an other is either $d_1=1$ or $d_2=2$, or not? (Wondering)
If this is true, is the optimal TSP-Tour the following?
$$(0,0)\rightarrow (1,0) \rightarrow (2,0) \rightarrow \dots \rightarrow (100,0)\rightarrow (103,0)\rightarrow (100,2) \rightarrow (99,2) \rightarrow \dots \rightarrow (1,2) \rightarrow (0,2) \rightarrow (0,0)$$
But how do we get from the point $(103,0)$ to the point $(100,2)$ ? (Wondering)
 

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  • #2
mathmari said:
Hey! :eek:

We consider the TSP in Grid-City.
The roads in Grid-City have the form of a grid, so that the intersection points can be described by an integer coordinate system.
The distance of $2$ points $C=(x,y)$ and $D=(x',y')$ is defined as $d(C,D)=|x-x'|+|y-y'|$.
An input for the TSP consists of $203$ points with the following coordinates:
$$(i,0), \text{ for } i=0, 1, \dots , 100, \\ (i,2), \text{ for } i=0, 1, \dots , 100, \\ (103, 0)$$
I want to give the optimal TSP-Tour. We have the following grid, or not?

(Wondering)

To find the optimal TSP-Tour from which point do we start? From which point we want? (Wondering)
If we choose one point to start, let's consider the $S=(0,0)$.
The second point will be either $A=(0,2)$ or $B=(1,0)$, right? Since $2=d(S,A)>d(S,B)=1$, the second point is $B=(1,0)$.
Or can we consider for the second point also the diagonal one, $(1,2)$ ? (Wondering)
Or is this not the correct way to find the optimal TSP-Tour? (Wondering)

When the roads are just the vertical and horizontal lines, we have that the distance of a point $(i,j)$ to an other is either $d_1=1$ or $d_2=2$, or not? (Wondering)
If this is true, is the optimal TSP-Tour the following?
$$(0,0)\rightarrow (1,0) \rightarrow (2,0) \rightarrow \dots \rightarrow (100,0)\rightarrow (103,0)\rightarrow (100,2) \rightarrow (99,2) \rightarrow \dots \rightarrow (1,2) \rightarrow (0,2) \rightarrow (0,0)$$
But how do we get from the point $(103,0)$ to the point $(100,2)$ ? (Wondering)

Hey mathmari! (Smile)

That looks all correct to me. (Nod)
In principle any point could be connected to any other point, but in this particular case your solution will be optimal.
We can get from $(103,0)$ to $(100,2)$ with a normal transition that has distance $5$. (Emo)
 
  • #3
I like Serena said:
In principle any point could be connected to any other point

So the road aren't just these gray lines, right? (Wondering)
View attachment 5792

Are the roads also the red lines:
View attachment 5793
? (Wondering)
I like Serena said:
in this particular case your solution will be optimal.

How do we know that? (Wondering)
 

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  • #4
mathmari said:
So the road aren't just these gray lines, right? (Wondering)


Are the roads also the red lines:

? (Wondering)

Yep! (Nod)
That's pretty much the problem with TSP - we have to consider all possible roads to find the solution, which is why it is so hard to find an optimal solution.

How do we know that? (Wondering)

It follows from common sense.
If we pick any of your red lines, the total path length will surely increase.
I'm not exactly sure how to prove it though. (Worried)
 
  • #5
I like Serena said:
That's pretty much the problem with TSP - we have to consider all possible roads to find the solution, which is why it is so hard to find an optimal solution.

Ah ok... (Thinking) After that I have to find the approximation for the TSP-Tour through the NEAREST-NEIGHBOR and then through the NEAREST-INSERTION with starting point $(0,0)$.

Do we get the following result through the NEAREST-NEIGHBOR?
$$(0,0)\rightarrow (1,0) \rightarrow (2,0) \rightarrow \dots \rightarrow (100,0)\rightarrow (100,2) \rightarrow (99,2) \rightarrow \dots \rightarrow (1,2) \rightarrow (0,2) \rightarrow (103,0) \rightarrow (0,0)$$
(Wondering)

Is the length of this Tour equal to $410$ ? (Wondering) The NEAREST-INSERTION algorithm is the following:
Code:
T <- {1} 
while |T|<n do 
   j <- vertex with minimal d(T,j), j notin T 
   insert j with minimal cost into T 
return T

So, we have the following:
T={(0,0)}
j=(1,0)
T={(0,0), (1,0)}
...
T={(0,0), (1,0), ... , (i,0), ... , (100,0), (100,2), ... , (j,2), ... , (1,2), (0,0)}
or not? (Wondering)

So, do we get the same result with both approximations? (Wondering)
 
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1. What is the purpose of studying the Optimal TSP-Tour in Grid-City?

The purpose of studying the Optimal TSP-Tour in Grid-City is to find the most efficient route for visiting all the points of interest in a city that is laid out in a grid pattern. This is important for various applications such as city planning, transportation, and logistics.

2. How is the Optimal TSP-Tour in Grid-City calculated?

The Optimal TSP-Tour in Grid-City is calculated using various algorithms, such as the Nearest Neighbor algorithm, the Greedy algorithm, and the Christofides algorithm. These algorithms use mathematical principles to find the shortest possible route that visits all the points in the grid city.

3. What are the benefits of finding the Optimal TSP-Tour in Grid-City?

Finding the Optimal TSP-Tour in Grid-City has several benefits, including reducing travel time and distance, improving transportation efficiency, and optimizing resource allocation. It can also lead to cost savings and improved productivity in various industries.

4. What challenges are involved in calculating the Optimal TSP-Tour in Grid-City?

One of the main challenges in calculating the Optimal TSP-Tour in Grid-City is the large number of possible routes, which makes it a computationally complex problem. Additionally, the grid structure of the city can also pose challenges, as it may restrict certain routes or create bottlenecks.

5. How can the Optimal TSP-Tour in Grid-City be applied in real-life situations?

The Optimal TSP-Tour in Grid-City can be applied in various real-life situations, such as planning delivery routes for packages or optimizing transportation routes for public transportation. It can also be used in city planning to determine the most efficient layout for roads and buildings, and in disaster management to plan evacuation routes.

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