K-means algorithm for capacitated clustering problem

Hello,

I want to perform K-means clustering algortihm for capacitated clustering problem. All the codes for k-means are about image processing so I couldn't figure out my problem.

Let's say I have 100 customers with x y coordinates and demands. I also have identical vehicles with a certain capacity C. I'll have clusters equal to (Total demand/C). I want to cluster the customers so that the total demand of each cluster does not exceed the vehicle capacity. The solution will appear as a binary matrix where rows represent customers and columns represent cluster numbers.

If you already have codes for this problem could you please share it with me or show me a way for how to do it?

I'd very much appreciate your help :)

[sakarya üniversitesi]

bende bu konuda çalışıyorum. bilgi paylaşımı yapabiliriz.

[Ronaldo]

I am working on this too and I have exactly the same problem. I am having dificulty in coding. If you did something can you help me too please. I would appreciate too.

[Image Analyst]

@Ronaldo this question was asked 10 years ago so it's not likely @Pinar will reply. You're best off asking your question in a new thread of your own.

Answer 1

[sakarya üniversitesi]

Bende bu konuda çalışıyorum. bilgi paylaşımı yapabiliriz.

[ibrahim alasmar]

hello, i want to ask something. im working on fuzzy c means and i couldnt find a performance index for this algorithm in matlab.Is there any index in matlab for it like indexes which used for K means like DB and Silhouette ? @ sakarya üniversitesi