I want implement polygon in c# using visual studio.Its one task of Google map part of my project.plz guide me.I have already done in c programing language using graphics function,is this similar for C#???
1) Please don't shout
2) Submit a specific problem, expose what you have done, what you expect and what you actually get.
Again, this forum is not here to do your work ; it is here to help on specific subjects/problems.
If you don't take the time to analyze your requirements by yourself, how do you expect we will do it for you ?
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Without your being more specific about your goals, and the problem, I don't think much can be said.
Most real-world examples of combinatorial optimization have constraints ... without which you have potentially infinite recursion.
For example ... assuming by "road map" you mean, literally, a map of highways, streets ... you would certainly not want to find combinations that are possible, but that involve doubling-back and repeating segments of the journey.
Are you trying to determine the shortest possible route ?
You may want to look at the infamous "travelling salesman" problem[^], where an attempt is made to find the shortest route which passes once through each city of a list of cities.
"Is it a fact - or have I dreamt it - that, by means of electricity, the world of matter has become a great nerve, vibrating thousands of miles in a breathless point of time? Rather, the round globe is a vast head, a brain, instinct with intelligence!" - Nathanial Hawthorne, House of the Seven Gables
First a Short intro to the Self Organizing Map
A Self Organizing Map (SOM) ,-sometimes called a Kohonen network-, maps multidimensional data onto a two dimensional map. A classic example is to classify colors by the Red, green and Blue (RGB) values. So if we have a large (10 000) set of randomly chosen colors, with different shades of, greens, reds, blues, pinks, etc. the SOM can map them on a 2-dimensional map where similar colors tend to end up on the same node on the map. If we chose a map with the dimensions 5 by 5 we get a map with 25 nodes. As an example the pink shades might end up in one corner of the map close to violet shades and the violets close to blue shades and so on. So similar colors tend to be close to each other. So if we wanted to classify those 10 000 colors in our dataset into 25 classes we could look at each colors node and use the information to se what class each of the colors belong to.
But how can we create clusters of several nodes based on their similarity to each other?