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Allow Location-Allocation to determine optimal locations for Existing Facilities?

LarryGaudieri

I am performing a series of analysis for our county's fire rescue. One question asked was it possible for me to allow Location-Allocation to determine the best locations (from existing facilities) to meet a data set of existing demand ( a year's worth of incident responses)?

I wasn't completely sure if it was possible or how the work flow would be. Again, taking existing fire stations, can Location-Allocation move those facilities to optimal locations to better meet the demand of the incidents?

Thanks to anyone who can help me out...

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Accepted answers

JaySandhu

It sounds like you are asking what is the best location for my fire stations based on where the incidents are happening. So in that case simply make up evenly spaced candidate facilities and solve for the same number of existing fire stations. Once you have a new solution you can closest facility to find the closest new facility from the existing ones and that will give you can idea how far to move! If it is under a certain threshold you could ignore the move.

If this is not your intended use case then clarify it a bit more.

Jay

All comments

MitchHolley1

Well, if you have an incident point layer, you could do a hot-spot analysis showing where the most of the incidents occur. From there you could do a network analysis on a road layer determining how far each fire engine could go from the fire station within __ minutes (need to determine specific amount of time). Then analyze the results to see if any fire stations could be moved, or another one built, to better served the needed areas.

Did I understand the question correctly? I hope this helps.

ChrisDonohue__GISP

Adding ESRI Network Analyst ExpertMelinda Morang to this thread. I suspect she has advice on this.

Chris Donohue, GISP

LarryGaudieri

Thank you Chris...it would be good to get as much feedback as possible.

LarryGaudieri

Mitch,

Thanks for the response. Yes, you understood exactly! I have a kernel density raster of the over goal times and have those stations isolated in or surrounding those hot spots. I've also performed service area analysis using the NavStreets network.

In the manual sense you described (which is a pretty good idea), I could do that. However, to demonstrate that the moves would in fact alleviate demand in certain locations in a repeatable process to support their position in a budget year...I'm hoping ArcGIS can do it faster and more accurately.

We have 44 stations and I could shift them (or at least the problematic ones) but I might detract performance or make it worse and that could get me into a game of hunt or peck for the best result. If there's no other statistical process then your idea would be the best bet.

Thanks again!

JaySandhu

If this is not your intended use case then clarify it a bit more.

Jay

LarryGaudieri

Thanks for the response Jay. Was beginning to think no one would respond. Your solution sounds logical but could you just clarify one part?

"solve for the same number of existing fire stations."

Does that mean that when the candidates are set, solve based on the required existing stations?

The rest is clear and once you reply, I'll set it and go.

Thanks again.

JaySandhu

Location-Allocation does not "move" an existing facility. It chooses the best set from a larger set of facilities. So having a good candidate set is important. And you can choose to load in the existing fire stations as candidates (not required). If you set them as required then the same location will be chosen. But if you set them as candidate and solve then you may get some original locations chosen (meaning they are in optimal location).

And you solve for the number of fire stations you want. If you had 10 existing and you still want 10 then solve for 10.

This is a very subjective decision as slight change to the problem setup can give you a different set of "optimal" locations. So in case you end up suggestions to move, you still have to evaluate how much "better" service/response time you will get. So you should solve with the existing fire stations and then solve for moving them and compare. All LA helps you with is generate alternatives that you need to evaluate in the context of some larger goal.

Not sure if I answered your question!

Jay Sandhu

LarryGaudieri

Yeah you did...it's excellent Jay. I really appreciate it. So, it's really

2 analysis: 1 with LA, the other with CF. Ok, if I send questions as I move

thru it?

Thanks again man..

ChrisDonohue__GISP

To state what Jay Sandhu is saying in a different way, is there a specific set of goals you are trying to achieve? For example, an advisory or regulatory limit on how fast apparatus can respond? I mention this as our City's Fire Department has a set response goal time they want to meet, and since our City is growing, they are constantly re-evaluating their coverage so they can see if that goal can continue to be met. Additionally, they need to plan out new Fire Stations so the new developments can also be covered while continuing to provide the same (or better) response times to existing areas. So knowing the goals and the context that goes with them is critical to formulating a good analysis.

Chris Donohue, GISP

LarryGaudieri

Thank you both for your responses. The criteria have been set for my project as on-scene goal times for emergency medical response of 7 minutes. This is just one aspect as we are master planning both operational and future planning aspects.

Reactive changes in operations, and exploratory planning and analysis for future siting. This particular exercise is to see how moving 2 apparatus (one each from 2 stations) to another 2 stations closer to a kernel density spot of over-goal responses would affect the "hot spot". So, it would be making those 2 stations more capable in response than surrounding stations.

I tried weighting the stations and running LA but the line solutions were in the hundred-thousands. I wasn't sure I could explain what had happened or demonstrate anything substantive on the result.

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