In the previous phase we imported the scenario, ran the Capacitated TO experiment, and observed results. In this phase we will add operating hours for our customers (limiting the possible delivery period) and compare the results.
We will assume that the Lidl stores can accept deliveries from 6 a.m. to 9 a.m., which means that the Gabrovo DC is supposed to visit all customers within this time period.
Add operating hours
- Click Data to open the scenario input data.
- Click All to see the full list of tables, then open the
Time windows table.
- Click Add to create a new record.
- Leave the default value of the Facility column, since it allows us to define operating hours for all customers.
- Click the Start Time cell and set the time to 6:00 AM
by either using the arrows on the right side or typing 6.
- In the same way define the end time in the End Time column:
- Set the time to 9:00
- Click the PM button to switch it to AM
- The Operation column defines if the specified Facility is supposed to receive (in case of a customer) or ship (in case of a site) the order. We will leave the default value of the column, since it defines the working hours for the customers.
Now we will set up the CTO experiment and run it. The experiment will consider the operating hours, which will affect the routes.
Set up the experiment and run it
- Navigate to the experiment's properties, by clicking Capacitated TO experiment in the experiment's section.
- Enable the Use time windows option by clicking the toggle button.
This will make the experiment consider the data from the Operating Hours table.
Click Run to run the experiment.
When the experiment is completed, proceed to analyze its results.
Observe the received results
- Navigate to the Optimization results page below the experiment view. This time the result contains 20 routes for 2 shipments.
- Type Sofia in the filter field of the Destination
column to see the list of routes in which it is used.
As you can see, there are two routes, one per shipment. The date of the shipment is specified in the Aggregation period column.
- Click the first record to have it displayed on the map.
The new route comprises three destinations (Sofia, Pernik, Blagoevgrad), while the previous result comprised 6 destinations (see the screenshot below).
- Switch to the Generated Paths page, group data per Shipment,
then click the
Add to comparison button to add this element to the comparison dashboard and name it
Result 2. We will get back to it later.
- Finally switch to the Generated Path Segments tab and group data per
This table contains details on each segment of every route. We are mostly interested in the data from the following columns:
- Origin - the point from which the vehicle sets off
- Destination - the point to which the vehicle arrives
- Distance, km - the distance between the two points
- Cost, USD - the transportation cost between the two points
- Arrival Time - the time when the vehicle arrived at destination point
- Scroll down until you see the Sofia customer in the Destination
Let us have a closer look at this route (see screenshot below):
- The vehicle set off from Gabrovo (our DC) and traveled 204.9 km to arrive at Sofia customer at 6 a.m.
- From Sofia customer the vehicle traveled to Pernik customer. The Arrival Time column shows that the vehicle arrived at 06:45 a.m., which means that It took 45 minutes to cover the Distance of 38.8 km.
- Then it arrived at Blagoevgrad customer at 08:23 am.
- And finally the last segment of this route is the returning segment. You can define it by looking at the Amount column cell on line 9, which shows that the vehicle did not carry any load on this segment. The vehicle traveled 307 km from Blagoevgrad customer back to Gabrovo, and arrived at the destination at 14:32.
Now we will compare the previous result with the current result.
- Navigate to the comparison dashboard by clicking Comparison below the result pages.
- Compare transportation costs in the Cost, USD column,
and the number of routes in the Destinations column.
As you can see, the number of routes has increased as well as the transportation costs. Overall the supply chain has become more expensive, but the good part is that we managed to visit all customers within the customer's operating hours.
We have completed the second phase of this tutorial. We added operating hours for our customers, ran the experiment and compared the received results.
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