 Many enterprises deal with vehicle routing challenges, so for example in this last mile delivery problem We need to deliver all of the packets to a number of locations in this region And as you can see as we add locations then optimal routes actually change The goal here is to minimize the delivery time to deliver all package with our vehicles available The best way to get started with Optoplanar is to clone the Optoplanar Quick Starts repository In this Quick Starts repository you will find currently four use cases and all of them are available in Quarkus with Java One of them the school time tabling Example is also available in Spring Boot with Java and in Quarkus with Kotlin right now if you want to run these examples simply run the run Quick Starts script, which I'm going to do right here right now and I've modified this to actually skip the build But you can now see if you go to localhost and we click Refresh we can actually see this coming up. This allows us to choose which example we want to run Right now, so let's run these cool time tabling example. This will actually run Quarkus def on on the background and Once that's ready, we'll take a look at it besides this cool time tabling example where we're assigning lessons to rooms into time slots We also have a facility location problem where we need to choose the best locations for new stores distribution centers Covid vaccination centers and so forth telcomasts and then we have a we're working on a maintenance scaling example for example for maintenance of airplanes or maintenance scaling of airplanes or Elevators and and so forth. We have a fun example around factorial layout, which is a Interesting video game and we have a couple of cases around vehicle routing and employee roster, which you might have already seen in the past So let me show let me take a look at the school time tabling one So in this we're going to assign the these lessons to these time slots in these rooms now when we click the solve button what you'll see is that Everything will be assigned to the first room into the first time slot and the reason for that is because I've disabled all of the constraints Currently there is no AI actually Happening or at least there's no effect to it But if you actually switch back to the source code and you say, okay, we don't want to have multiple Lessons in the rate same room at the same time. We can actually just add this constraint. This is how it looks I'm not going to go into the implementation right now But if we now go back over here, we refresh this thanks to quark as this takes just an instance We solve this problem You will see that opt-up and now doesn't assign two room two lessons in the same room at the same time So we've actually solved that problem However, if you look from a teacher's point of view, you will still see well It looks good for a teacher's apparently but if you look for student groups You will still see that we have two Student groups the nine grade here in the same room at the same time So let's fix that too and actually there could be still teacher conflicts So I'm going to mean I'll fix this one too. So I'm going to enable these constraints And if we go back over here, we do another refresh We do another solve we can see the results of these AI constraints actually in this Schedules now we get a different schedule as we did before but still all of the rooms But there is no room conflicts. We now go to the students groups You can see there's no student group conflicts And if you go to the teachers, you can see there's no conflicts there either. However, it's not really a compact Schedule for the teachers yet. You can see many gaps for a particular for each teacher You can see gaps in their schedule and that too, of course, we can fix with what we call soft constraints And so here I have a number of soft constraints Let me take the teacher time efficiency constraint added in and let's take a look what that does for us So we refresh the page again. We solve again. We take a look at the teacher effect And you can see we get much more compact Schedules for the teachers for more information visit optoplanar.org