Generate an optimal picking plan for completing a set of orders.
-
Install Java and Maven, for example with Sdkman:
$ sdk install java $ sdk install maven
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Git clone the timefold-quickstarts repo and navigate to this directory:
$ git clone https://github.com/TimefoldAI/timefold-quickstarts.git ... $ cd timefold-quickstarts/java/order-picking
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Start the application with Maven:
$ mvn quarkus:dev
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Visit http://localhost:8080 in your browser.
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Click on the Solve button.
Then try live coding:
-
Make some changes in the source code.
-
Refresh your browser (F5).
Notice that those changes are immediately in effect.
When you’re done iterating in quarkus:dev
mode,
package the application to run as a conventional jar file.
-
Compile it with Maven:
$ mvn package
-
Run it:
$ java -jar ./target/quarkus-app/quarkus-run.jar
NoteTo run it on port 8081 instead, add
-Dquarkus.http.port=8081
. -
Visit http://localhost:8080 in your browser.
-
Click on the Solve button.
-
Build a container image:
$ mvn package -Dcontainer
The container image name
-
Run a container:
$ docker run -p 8080:8080 --rm $USER/order-picking:1.0-SNAPSHOT
To increase startup performance for serverless deployments, build the application as a native executable:
-
Compile it natively. This takes a few minutes:
$ mvn package -Dnative -DskipTests
-
Run the native executable:
$ ./target/*-runner
-
Visit http://localhost:8080 in your browser.
-
Click on the Solve button.
Visit timefold.ai.