How Many Possible Routes in the Traveling Salesman Problem?

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In summary, the traveling salesman problem involves finding the shortest route to connect a group of points out of all possible routes. There is no general math formula for calculating the total number of possible routes, but a simple formula for the number of routes connecting N points is (N-1)!/2. This formula has not been widely published as it is easily derived and does not provide any further insight into the problem.
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O Great One
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The traveling salesman problem is where you have to figure out the shortest route connecting a group of points out of all possible routes. I haven't seen a general math formula to figure out the total number of possible routes given a set of points so I tried to come up with one myself and here's what I got. Let's say that there's four points and you want to know what the total number of possible different routes there are that will connect all four points. Let's assume that the points are numbered 1, 2, 3, and 4. Then these 8 routes are all the same.
12341 23412 34123 41234
14321 21432 32143 43214

The route inbetween the end points can be sequenced in (N-1)! ways and there are N different beginning and endpoints. But, each sequence has N*2 routes that are equivalent so we must divide by that. So this is what we get where N is the number of points:

((N-1)!*N)/(N*2)

We put in 3 points and we get 1 route.
We put in 4 points and we get 3 routes.

The formula seems to be correct and seems to work but I haven't seen it anywhere. Comments?
 
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Your expression should simplify to (N-1)!/2 and does look correct. Perhaps the reason this is not found anywhere is that it is trivially simple to see and still has no bearing on the problem other than to show that it is NP complete.
 
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Your formula for calculating the number of possible routes in the traveling salesman problem is correct. This is known as the factorial formula and is commonly used in combinatorics to calculate the number of permutations or combinations. It is also used in other mathematical fields such as probability and statistics.

Your formula takes into account the fact that there are multiple ways to arrange the points in a route, but some of these arrangements are equivalent. This is known as overcounting and can lead to incorrect results if not taken into consideration.

It is great that you have tried to come up with a formula yourself and have found it to be correct. However, this formula is well-known and has been used in various applications of the traveling salesman problem. So, you may not have seen it explicitly mentioned as the "traveling salesman formula", but it is a fundamental concept in solving this problem.

Overall, your understanding and application of the formula is accurate and it is good to see that you have a grasp on this important concept in the traveling salesman problem. Keep exploring and learning more about this problem, as it has many real-world applications in fields such as logistics, transportation, and computer science.
 

FAQ: How Many Possible Routes in the Traveling Salesman Problem?

What is the Traveling Salesman Formula?

The Traveling Salesman Formula, also known as the Traveling Salesman Problem (TSP), is a mathematical problem that seeks to find the most efficient route for a salesman to travel to a given set of cities and return to the starting point, while visiting each city only once.

How does the Traveling Salesman Formula work?

The Traveling Salesman Formula works by creating a graph of the cities to be visited, where each city is represented as a node and the distances between them are represented as edges. The formula then calculates all possible routes and determines the shortest one using algorithms like brute force, dynamic programming, or heuristic methods.

What is the significance of the Traveling Salesman Formula?

The Traveling Salesman Formula has significant applications in various fields, including logistics, transportation, genetics, and computer science. It helps in optimizing routes and minimizing costs, which can save time, resources, and money in real-world scenarios.

What are the limitations of the Traveling Salesman Formula?

The Traveling Salesman Formula becomes increasingly complex and time-consuming as the number of cities increases. It is considered an NP-hard problem, which means that there is no known efficient algorithm to solve it in polynomial time. Therefore, for large-scale problems, finding an optimal solution may not be feasible.

Are there any real-world applications of the Traveling Salesman Formula?

Yes, the Traveling Salesman Formula has numerous real-world applications, including route planning for delivery services, scheduling and optimization in manufacturing and supply chain management, and DNA sequencing in genetics. It is also used in the development of computer algorithms and in mathematical research.

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