topic Re: Using Maximize Capacitated Coverage Effectively in Spatial Data Science Questions

Using Maximize Capacitated Coverage Effectively

JacquelynPutnam — Thu, 13 Aug 2015 14:26:15 GMT

Hey everyone! I am currently trying to use the maximize capacitated coverage problem solver of location-allocation to allot a study area population to emergency shelters. I have a layer of approximately 250 shelters, all of which have a capacity as large as 800 and as small as 10. My study area is quite large; at present I have 1268 census block group cetroids. Obviously each demand point contains a multitude of census data such as raw population. I would like to allocate population to the shelter that is closest by drive time, but am having trouble because the demand points cannot be apportioned to the facility, it's all or nothing. My end result is very unrealistic because most shelters reach all the way out into rural areas where the demand point's population is small, bypassing literally thousands of others who would reach the shelter first.

How can I rectify this? From the other posts in the forum it would appear I may have to break up the demand points into smaller populations. If so, how do I want to go about this? Create Random Points where the population contained in the census block group is the number of points created inside the block group polygon?

Thanks in advance for any insight you may have. I'm at all total loss!

Re: Using Maximize Capacitated Coverage Effectively

JaySandhu — Thu, 13 Aug 2015 15:38:33 GMT

You are right that it is "all or nothing" allocation for each demand point. Besides the approach you mentioned about creating random points inside the census polygon, you could add the same demand point multiple times with less demand. Let's say you have a demand location with 100 units of demand. You could add that same location ten times with a a demand of 10. These points will be sitting on top of each other but they may be allocated to different facilities as needed.

Jay Sandhu

Re: Using Maximize Capacitated Coverage Effectively

MelindaMorang — Thu, 13 Aug 2015 15:42:54 GMT

What about using census blocks instead of block groups?

Re: Using Maximize Capacitated Coverage Effectively

FaroukUmar — Fri, 10 Aug 2018 03:42:01 GMT

Please, is there any way to create these multiple points of lower demand in Arc GIS? What is the best and quickest way to do it?

Re: Using Maximize Capacitated Coverage Effectively

JaySandhu — Fri, 10 Aug 2018 16:39:28 GMT

You can simply load the points to the Location-Allocation layer multiple times! Make sure to load them with lower demand. For example if you load them five times, then make sure the demand is 5 times less.

Or you can start editing the point feature class, copy the points and paste them again as many times as you want.

Jay Sandhu

Re: Using Maximize Capacitated Coverage Effectively

FaroukUmar — Wed, 15 Aug 2018 04:39:05 GMT

Thank you very much. I have made the multiple demand points (29001). However, the maximise capacitated coverage analysis takes about 30 minutes to run and sometimes doesn't run. The 29001 demand points are loaded within 3minutes without any problem. The network dataset has a spatial index. Could this be due to the number of demand points I have? If I use fewer demand points it works perfectly. What is the solution, please?

Re: Using Maximize Capacitated Coverage Effectively

JaySandhu — Wed, 15 Aug 2018 15:40:42 GMT

When you say that it does not run sometimes, do you get an error message or it hangs? What error do you get?

You can try to add a distance/time cutoff to cut down on the amount of searching. For example if your demand is spread out over 10 miles and you are allocating 10 facilities, then perhaps a cutoff of 3 or 4 miles should be enough. It basically means a facility will not search beyond that distance for available demand.

Jay Sandhu

Re: Using Maximize Capacitated Coverage Effectively

FaroukUmar — Wed, 15 Aug 2018 19:11:28 GMT

I am using 5000 and sometimes 10,000 metres as the distance cutoff. The problem is when I click the solve button, and it takes about 30minutes to locate the facilities. In some cases, it stays at 0% without progressing.

Re: Using Maximize Capacitated Coverage Effectively

JaySandhu — Wed, 15 Aug 2018 20:15:22 GMT

The amount of time needed to solve location-allocation will depend on the number of demand points, number of candidates and how many facilities you are choosing to locate. So it can definitely take a long time if the problem size is big. How many demand and candidates do you have and how many are choosing?

Jay

Re: Using Maximize Capacitated Coverage Effectively

FaroukUmar — Wed, 15 Aug 2018 20:41:11 GMT

I have 838 required facilities and 350 candidate facilities. I am choosing 1000 facilities. I also have 29000 demands points after breaking the original ones to points of lower value.

Re: Using Maximize Capacitated Coverage Effectively

JaySandhu — Wed, 15 Aug 2018 22:00:07 GMT

So 1188 facilities choose 1000 (even when 838 are fixed) are a lot of combinations! And solving for capacity does add another layer of complexity. So it can take some time to find a solution. I cannot estimate the time needed (based on what hardware/memory/etc that you are using), but it could be a while!

Jay Sandhu

Re: Using Maximize Capacitated Coverage Effectively

GarrettMelvin — Mon, 20 Jan 2020 16:17:15 GMT

Is your network dataset stored on disk, or on a network? We have streemap premium, and when it was stored on our network, processing time was very long. I moved the network dataset to an external hard drive with a super speed USB cord, and processing time drastically decreased.