Traveling salesman movie review part 4 – hiring the right salesmen by using graph theory

traveling salesman movie

The Traveling Salesman is a 1921 American comedy starring Fatty Arbuckle. It’s loosely based on a late 1908 play, The Traveling Salesman by James Grant Forbes. Frank McIntyre also appeared in the film. In the film, he plays the title role.

The movie begins by explaining that the title character is an euclidean traveling salesman problem solving expert. He solves different traveling salesman problems while traveling from one city to another, usually via a long suitcase. Each time he solves the original traveling salesman problem, he makes a profit from the alternate city. Although the story is very funny, the symmetric triangles and the use of an object-oriented programming language makes the movie quite entertaining.

The movie then shows the fictional tale of George Stavroust, a euclidean who travels from town to town solving different traveling salesman problems. At each town, he presents his case to the local police captain. The only problem with this method is that each time he presents his case, the case gets easier. However, when the case becomes harder, George will have to travel to solve the problem once more. Eventually, after traveling many times over the same region, George will be able to solve the problem of all traveling salesman problems.

The movie then uses the idea of a dynamic programming language called SIMBL (Symbolic Semantic Binary Languages) to create a simulation of cities in which the SIMBL algorithm operates. In this way, we can see how the traveling salesman tour starts. First, there are some random places where the algorithm sends its program. Then, these starting points are visited by the salesman. And after it, they go to the next starting point and so on until the whole region has been visited. However, with this, something is wrong as the traveling salesman cannot solve all the cases in this region and as a result, he is forced to move on.

Therefore, the movie then shows what the algorithm does after George has solved the first case. It moves on to the second region and repeats the process there. The third region also has the problem of the shortest possible route. To handle this, the algorithm uses a greedy algorithm. This means it will take the shortest possible route through all of the regions and then calculate the probability of all these routes. After this, it will choose the best solution in terms of the shortest possible route through all the regions.

Another interesting part in the movie is when the algorithm will travel over the graph in the above example starting from the left and going right to the right. The reason for doing this is to find out which of the shortest paths exists between the two end points. And finally, the last region is called the upper bound. In this region, the algorithm will take the left closest solution that exists between the two start and end points and the algorithm guarantees that this solution exists. Thus, the travelling salesman problem is solved using the most appropriate method.

Now that you know how to solve the traveling salesman problem using heuristics, you may be wondering why the movie called "The Traveling salesman" uses some of the optimization methods. Well, according to the research of behavioral scientists and psychologists, we use these optimization methods to solve problems and then explain why these methods are important. They say that if we can explain why an optima exists or why it is the best solution, people will be able to apply it in their daily lives and understand the concept better. So, using approximate calculations and heuristics are actually part of these psychological explanations.

As a conclusion, all this is very interesting. Of course, it is based on some psychological principles. Nevertheless, it is a good watch especially if you have not watched the movie. We can conclude that the movie uses some of the more advanced methods and we can safely conclude that it gives you a good education about finding optimum solutions using graphs and graph theory. It gives the impression that the movie is more about mathematics and it makes you think what would have happened if we use some of our modern mathematics tools like graphs and heuristics, and also explains some psychological principles such as the idea of connections and vertices.


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