Given the distance/travelTime data for each edge, the shortest/fastest path
in a typical network  is often unique and thus all algorithms reach the
same result (manhatten grid networks are an obvious exception to this).
Therefore it does not matter which algorithm you use as long as they use
the same inputs.
Thus, I was trying to understand what difference you would expect from
using non-sumo algorithms.

Am Di., 25. Feb. 2020 um 05:02 Uhr schrieb Raheleh Zarei <
[email protected]>:

> I am not sure if I understand the first paragraph of your email. The
> algorithms are shortest/fastest path finders(I call them non-sumo
> algorithms). Actually the thing I want to do is as follow:
> -Import map of a city as road network
> -Make some source and target points based on the map
> -Run random number of source-target queries between these source and
> target points and for every query (or in a time interval for example every
> 20 second) get the current situation of the network (like the travel time
> of edges because it might have changed due to heavy traffic in some edges)
> and find the shortest path/fastest using non-sumo algorithms.
> -calculate the path found (time/distance) by non-sumo algorithms for each
> source-target query and also average of time-distance for the whole s-t
> queries during simulation.
>
> Thanks for your help,
> Raheleh
>
>
>
> On Mon, Feb 24, 2020 at 2:11 AM Jakob Erdmann <[email protected]>
> wrote:
>
>> It depends on what these other algorithms are. If they are also
>> shortest/fastest path finders that it would be sufficient to alter the
>> weights/travel times assigned to the network edges (via TraCI or xml
>> inputs) and keep using the sumo algorithms.
>> You could also let these other algorithms compute their routes externally
>> and then alter the routes in the simulation (via TraCI or xml inputs).
>> regards,
>> Jakob
>>
>> Am Mo., 24. Feb. 2020 um 02:58 Uhr schrieb Raheleh Zarei <
>> [email protected]>:
>>
>>> Thanks for your explanation.
>>> Yes, you are right. So, what you suggest to do if I want to compare
>>> other routing algorithms with SUMO routing algorithms from traffic
>>> efficiency point of view?
>>> Do I need to develop SUMO source code and add other routing algorithms,
>>> or there is another way I can call these algorithms inside SUMO.
>>>
>>> Thanks for your time and help.
>>> Raheleh
>>>
>>> On Tue, Feb 18, 2020 at 3:57 PM Jakob Erdmann <[email protected]>
>>> wrote:
>>>
>>>> Libsumo is useful if you need at lot of interaction between your code
>>>> and sumo because it reduce communication overhead compared to TraCI.
>>>> If you are comparing the algorithms in terms of overall traffic
>>>> efficiency then most of the time is spent on simulation rather than routing
>>>> so you won't need Libsumo.
>>>> If you are repeatedly calling the sumo routers to compare the found
>>>> routes with your own routes then it makes more sense.
>>>> For details, see https://sumo.dlr.de/docs/Libsumo.html
>>>> regards,
>>>> Jakob
>>>>
>>>> Am Mo., 17. Feb. 2020 um 10:19 Uhr schrieb Raheleh Zarei <
>>>> [email protected]>:
>>>>
>>>>> Hello,
>>>>>
>>>>> I would like to test two routing algorithms using SUMO as a framework
>>>>> for comparing these algorithms. Inside the program of these algorithms
>>>>> (written in C++ in Linux), I need to call SUMO, start it, get the required
>>>>> variables and reports and then close it and see the results. What do you
>>>>> suggest for this? Do you think using Libsumo is a good idea? and if
>>>>> yes what's the procedure of using it.
>>>>>
>>>>> Best,
>>>>> Raheleh
>>>>> --
>>>>> *RAZ*
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>>> --
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>
> --
> *RAZ*
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