I need to make clusters of exactly 50 points based on location to be used later as an input layer in VRP. No other attribute available on the basis of which they can be grouped.
Grouping analysis doesn't give exactly the same no. Appreciate if someone can help. geonet geo-processing tools point statistics network geoprocessing vrp networkanalyst
Actually, the global standard is that we can cover maximum 50 outlets/day using one vehicle, not more/less than that. let's say if a salesman is covering a chunk of 50 outlets on monday, then on tuesday he needs to start visiting the next nearest chunk of 50 outlets, starting from one end and sweeping the entire area.
This can't be controlled in VRP even if I specify that the max order count is 50, the system incorporates all the parameters like start, end time, demand, capacity, max travelling time to generate the route, which doesn't give us the exact 50 outlets. Also, if I input all the data, the routes that are generated are overlapping, hence routes are not optimized. so I was looking if somehow I get clusters of 50 outlets, I can preserve the route and relative sequence in VRP.
There is a similar question here: Group every near 50 points together If you scroll down towards the end of the thread you will find an answer by Curtis Price that provided a solution that might work for you.
I gave it a try on your dataset and attached the result for you to examine. I added an extra field with the classes.
Hi, I have implemented the same, but I'm not getting the results that you have attached.
This is what I did.
Input: Sample Data
Output: Output specification
Spatial Sort Method : UR(By default)
Added a new field and calculated it using the formula in python :
The groups i'm getting are random, not nearest neighbours.
can you tell me what I'm missing here.
I implemented the process on another dataset.
I'm attaching the snapshot for reference, where you can clearly see two different clusters for blue pushpins. The same pattern can be observed in other cases. I don't get the logic behind it.
Yes, I agree, if you used the peano search that pattern shouldn't be the result. This is a featureclass you are working on isn't it? Is there anything strange about it?