Optimized Drive Time Analysis

Question

Good Day

I am looking for a workflow that will allow me to optimize drive time service areas that will cover a geographic area. I only have the drive time criteria and geographic area boundary as input. I am trying to figure out how I would create the dispatch points so that I have maximum coverage but minimize the number of dispatch areas. I have some ideas but a lot of it comes down to trial and error.

Thanks

Bruce

BruceBurwell1 · Answer

Thanks for these suggestions.I am going to look at the location allocation solution.

DavidPike · Answer

Possibly https://pro.arcgis.com/en/pro-app/latest/help/analysis/networks/location-allocation-analysis-layer.htm

I'd imagine that you have a set of pre-determined supply points and then attempt to maximise coverage and minimize facilities.  Considering the computation involved, I would absolutely not use demand points as individual houses/businesses etc, I would look to aggregate them into weighted points (the larger the aggregation area, the faster it will run, but also be less accurate, so probably look for the goldilocks zone, there could still also be so many combinations that it still takes a life age of the universe to run).

If you don't have a set of predetermined facility locations, I would probably generate a regular grid of points, again being aware that the combinatorics of those points could get horrendously large.

This is just what I have in my head rather than a defined workflow I'm sure would work.

JaySandhu · Answer

The Location-Allocation capabilities of Network Analyst helps you pick dispatch locations (warehouses, etc.), to service a set of demand locations. So you should be able to use that for your use case.

You can read more about it here: Location-allocation analysis layer—ArcGIS Pro | Documentation

You can try out the Tutorials here: Network Analyst tutorials—ArcGIS Pro | Documentation

You will have to think about how you will use your data like boundaries and turn them into inputs for this solver. Let me know if you want to discuss this more once you have had a chance to read up on it.

Jay Sandhu