Video

Yes, see ConstraintConfiguration in the OptaPlanner/Timefold docs.

Timefold (= OptaPlanner++) is often used for that kind of cases. Model wise you let it decided the route without recharging, and force "just in time automatic nearest recharging" through a shadow variable. Basically if I can get from start to Z to A without recharging, fine. If I can't get to D any more without recharging, automatically active the shadow var on D to state that it will first recharge at the nearest recharger (B).

What are you missing in the document? Also take a look at the timefold-quickstarts repo, directory use-cases/vehicle-routing-time-windows etc

If you run it from source, you can edit the source code. In Timefold quickstarts we're making this easier by providing curl commands to send the json dataset to the VRP rest API. Revists are possible, but you'll currently have to add that revisit constrain yourself.

In optaweb-vehilce-routing, it's a matter of fetching the travelDuration matrix (or distance matrix) on basis of a bicycle instead of a car.

In optaweb-vehicle-routing demo application, run runLocally.sh --help to see info on how to select your geographical region.

There's are good getting started guides on the OptaPlanner website: click on the big blue button there. There are also getting started videos in this youtube channel.

In the optaplanner-quickstarts repo, take a look at the facility-location (see also the video on this youtube channel) and vehicle-routing quickstarts. You'll need to tweak the constraints depending on your needs. For example, you could add a soft constraint that penalizes the distance between every pair of assignments in the same territory. For questions/discussions on that, open a thread on Stackoverflow or our forum: www.optaplanner.org/community/getHelp.html

OptaPlanner doesn't consume DMN. Our sibling project, Drools (drools.org) does support DMN decision tables. Give it a try! As for generating DMN with OptaPlanner, it depends. It could be a good fit. Please open a discussion on OptaPlanner's forum (optaplanner.org -> Get Help).

@@GeoffreyOptaPlanner thanks. I should have been clearer. I'm familiar with Drools. It would be good see Optaplanner used to optimise the settings used in a DMN decision table.

@@magick93 That could be a good fit indeed - please open a thread on Stackoverflow or our forum: www.optaplanner.org/community/getHelp.html

You're welcome :)

@@geoffreydesmet1043 Thank you sir. I'm done with the project and it's working fine 😎

Please open a StackOverflow question: www.optaplanner.org/community/getHelp.html - Look at SolverManager.create().

@@GeoffreyDeSmet okk sure thanks for replying really loved your session

optaplanner developer ?

Does "mvn clean install" work?

@@GeoffreyDeSmet Hi Geoffrey thank you for your response. Finally a managed to install it. The problem was on me lack of expertise side. The problem I have now is that the generated project with Quarkus I made has some different dependencies from the one you generated for the tutorial. So I'm stack.

@@nettogrowthpartners9567 The dependencies changed from io.quarkus:quarkus-optaplanner to org.optaplanner:optaplanner-quarkus Follow the guide here: quarkus.io/guides/optaplanner Or the source code here: github.com/kiegroup/optaplanner-quickstarts

@@GeoffreyDeSmet Thanks a lot Geoffrey!

Then I guess there's situations where one lesson date and time might already be locked in for some reason... would this solution work in that situation?

@@idev247 We call this locking down "pinning". It's very easy to do in OptaPlanner, just add a boolean field with an @PlanningPin annotation on the Lesson class. If it's true, optaplanner will not reassign that lesson instance to another room or timeslot - but it will of course take it into account for the constraints.

For lessons of variable lenght, you need to adjust the model. In the conference scheduling example the talks are of variable length (for example labs take 2 hours, but normal sessions 1 hour), but because both talk types have their own set of timeslots, it hardly impacts the model. In what you're describing, that's different: that's the "time grain design pattern": see docs and the meeting scheduling example.

@@GeoffreyDeSmet Thanks getting back to me Goeffrey! Will look at the docs for "time grain design pattern"/meeting schedule example

For example unable to add a new parameter even though the input format is given. Is there a document which gives example calls or give details of parameters that are mandatory - { "draftLength": 0, "firstDraftDate": "string", "id": 0, "lastHistoricDate": "string", "publishLength": 0, "publishNotice": 0, "rotationLength": 0, "tenant": { "id": 0, "name": "string", "version": 0 }, "tenantId": 0, "timeZone": { "id": "string", "rules": { "fixedOffset": true, "transitionRules": [ { "dayOfMonthIndicator": 0, "dayOfWeek": "MONDAY", "localTime": { "hour": 0, "minute": 0, "nano": 0, "second": 0 }, "midnightEndOfDay": true, "month": "JANUARY", "offsetAfter": { "id": "string", "totalSeconds": 0 }, "offsetBefore": { "id": "string", "totalSeconds": 0 }, "standardOffset": { "id": "string", "totalSeconds": 0 }, "timeDefinition": "UTC" } ], "transitions": [ { "dateTimeAfter": "2020-07-29T18:40:19.295Z", "dateTimeBefore": "2020-07-29T18:40:19.295Z", "duration": { "nano": 0, "negative": true, "seconds": 0, "units": [ { "dateBased": true, "durationEstimated": true, "timeBased": true } ], "zero": true }, "gap": true, "instant": "2020-07-29T18:40:19.295Z", "offsetAfter": { "id": "string", "totalSeconds": 0 }, "offsetBefore": { "id": "string", "totalSeconds": 0 }, "overlap": true } ] } }, "unplannedRotationOffset": 0, "version": 0 }ble to add a new tenant even

Thank you very much @@GeoffreyOptaPlanner ! Funny that in the repository search does not match file titles. github.com/kiegroup/optaplanner/search?q=patientAdmissionScheduleSolverConfig&type=Code