PTV Group - Logistics Forum

Posted: **Mon Jul 24, 2023 5:40 pm**

Hi there,

I've been asked for some recommendation for a nice little usecase - as I created another testclient for this let me share my results with you.
Here's the story:

Imagine you are returning from a long distance trip with an empty vehicle. At that stage you already know the distance and traveltime of the blue relation based on a distance matrix or 1:1 route. Let's call these KPIs the "reference" for the next steps.
Now within your horizon there's a bunch of potential pickup-delivery orders you could go for.

FTL somewhere around you

Question: which one can you add to your empty return trip with the least efforts?

First I created a dummy input tour with the blue relation and enforced the pickup location to be FIRST_CUSTOMER_STOP and the delivery as LAST_CUSTOMER_STOP. Then I performed a FindChangeToursProposalsRequest for each pickup delivery candidate:
Code: Select all
```
FindChangeToursProposalsRequest findChangeToursProposalsRequest = new FindChangeToursProposalsRequest
{
      proposalsOptions = new ChangeToursProposalsOptions { },
      proposalsQuery = new InsertionPositionsForOrdersQuery
      {
         targetVehicleIds = new string[] { "vehicle" },
         orderIds = new string[] { 
         orderId
      },
      storedRequestId = toursResponse.storedRequestId
   }
};
```
The output of these calls gives me the decision criteria to compare the impact of the potential "changeToursActions" compared to the "reference" KPIs.

All potential inserts
I then used the confirmed changeToursActions to compute the complete insertion moves.

A specific selection
This approach gives a very good result in terms of quality but it also "wastes" number of transactions with a square complexity. This is why I evaluated an alternative approach below.

For the alternative approach I didn't use the xTour module but a linear growing process based on three contributing factors per candidate:
- The leg from the global starting location to a candidates pickup
- the leg from the candidates pickup to the candidates delivery
- the leg from the candidates delivery to the global delivery.
So more or less this is based on 3 rectangular matrices:
- [1:N] : from the global pickup to all candidates pickups
- N-times [1:1] : from each candidates pickup to its own delivery (this info is supposed to be available once such a candidate is inserted into the global pool!)
- finally a [N:1] matric from each candidates delivery to the global delivery
. The output looks pretty much the same compared to the approach above but there's a downsight: you can't apply break- and restrules

Instead of the complete distance matrix based "tour optimization" you can go for a linear growing approach
NO matter what approach you want to go for: it probably makes sense to define some simple filter criteria to not consider changeTours which exceed some threshold value, e.g. based on a relative "increase" of traveltime or distance caused by the detour.

Client filter based on relative distance... threshold 75%
Last but not least you could evaluate to define some other criteria in advance which reduces the input candidates for that little process, e.g. based on corridor searches / reachable areas.

The corridor of 100km along the reoute - helpful for some quick prefiltering "before" the candidates are forwarded to the "expensive" process.

PS: Of course I already calculated all the underlying info based on a xDima2.CreateDistanceMatrix request...

PTV Group - Logistics Forum

Backhaul calculation / Freight exchange

Backhaul calculation / Freight exchange