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Problema de Roteamento de Veículos vs Alocação de Localização

RobertFord1

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Obrigado antecipadamente por toda a ajuda.<\/P>

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Estou tentando criar um modelo para adicionar pessoal a certas estações de bombeiros e como isso mudaria a dinâmica possível de resposta. Eu pesquisei sobre o uso do VRP, mas parece muito complexo para o que eu estou buscando.<\/P>

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Queremos saber se, ao adicionarmos um aparelho extra a uma estação de bombeiros, essa estação atenderia mais chamadas 911 do que as estações ao redor. Quero usar dados históricos e dizer que, se adicionarmos este veículo, ele adicionará este número de atendimentos a essa estação enquanto também alivia este número de atendimentos das estações vizinhas. <\/P>

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Então, em relação ao VRP, os "Depots" seriam minhas estações de bombeiros enquanto meus "Orders" seriam as chamadas 911 na área. Quanto à alocação de localização, como eu modelaria as capacidades de cada estação de bombeiros? Por exemplo, digamos que uma estação tenha 2 caminhões enquanto todas as outras têm 1. A estação com 2 caminhões pode responder a mais eventos do que aquelas com um. Como eu poderia modelar isso? <\/SPAN><\/P><\/P>Qualquer ideia é muito apreciada! <\/P><\/BODY><\/HTML>

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RyuLippmann1

Hi Robert,

I'm interested in this as I'm modelling logistics for reef restoration over the Great Barrier Reef.

There are a few intervention strategies, and similarities with your model and problem here.

I am contacting you to see whether there's a way you could share your model/paper/findings with me so that I can reference it in my work.

Thanks 🙂 Ryu

RobertFord1

Also I keep getting the following warning and the VRP will not solve:

"Warning: Depots, Routes, Orders and Breaks contain time windows with dates but the DefaultDate value does not have a date.
Error: Invalid input in the NA classes."

RobertFord1

Hi Heather,

Could I use collect events for our historical data and give an address with more than 1 event a weight equal to the number of events that happened there? This would cut down on the number of orders quite a bit but I would imagine it would still be tens of thousands of points.

Thanks!

HeatherMoe

Hi Robert,

The VRP Solver would work best at a per day modeling. Once you get a set up you are happy with you could get a model builder or python script to make a layer for each day of the year and then look at the aggregates for seeing how the changes you make affect over the long term. 150,000 points is definitely too much for one VRP solve though.

Heather

RobertFord1

Thank you Heather! This gets the ball rolling! I would like to model 1 year worth of data which is close to 150,000 points. Would this be too much for VRP? Thanks!

JoeBorgione

Cross posted here: https://community.esri.com/thread/202953-location-allocation-or-vehicle-routing-problem

HeatherMoe

Hi Robert,

For getting started with the VRP solver you can work through the following tutorial. It will help you understand how the pieces fit together.

Exercise 7: Servicing a set of orders with a fleet of vehicles—Help | ArcGIS Desktop

As for your specifics. Using historical data makes a lot of sense for simulating out a day of 911 responses. You are correct in thinking the fire houses should be modeled as the depots and the calls would be the orders. The vehicles are then modeled as routes. The routes need a starting and ending depot specified so in your case you would create a route for each truck and then separate out the trucks to the fire stations by identifying which depot they start and end their day. Once you get things set up you can start moving the trucks to different fire stations and see how the work gets moved around from one simulation to the next.

With the historical data from one day, I think you would need to use the time windows on the orders to signify what time of day that phone call came in and needed to be taken care off. You mention that on a particular day you don't know when the calls will come which is okay in this case because you are wanting to simulate a day that has already occurred and so you want the times to match that particular day. This is probably not the right tool as it is currently designed to help with solving the dispatching problem in a live setting. Besides the time windows that you mentioned another thing you should add in is the service time for the incidents. This would be how long the fire truck was at the location. This will help model how long that vehicle is busy and unable to go to a different location.

I'm definitely not in the fire fighting business but some aspects of this problem that I can think of that might make the modeling more difficult are as follows. I believe it is fairly common for the fire truck to go to one incident and then back to the fire house waiting for the next call to come in. To account for the going back to the fire house you can make the fire houses as route renewals also and then specify a capacity of one for the routes and give each order a pickup quantity of one. This would make the fire trucks have to get "re-supplied" between calls and go back to the firehouse to match the way they typically operate.

Another concern is if a fire is big enough to need more then one fire truck to respond at a time you would need to model in the number of trucks that were needed as separate orders with the same time window and service time at the same location. In this case each order would have the delivery quantity that would max out a fire trucks capacity and so several routes would go to that location at the same time.

A lot to think about but give it a try and let me know how it goes and if you have more questions.

Heather

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