ge0ffrey

7 ms·

31.
by ge0ffrey 3y ago
There are little to no commits on the optaplanner repo since May 2023, apart from CI/build changes.
32.
by ge0ffrey 3y ago
Could you elaborate on how OptaPlanner/Timefold wasn't ergonomic? I 'd love to understand this better, so we can improve it in Timefold Community. To help deal with new problems, we're creating out-of-the-box quickstarts
33.
by ge0ffrey 3y ago
I once optimized Factorio's belts with OptaPlanner (now Timefold.ai), our open source metaheuristics solver in Java. The source code is still here: https://github.com/kiegroup/optaplanner-quickstarts/tree&#x
34.
by ge0ffrey 3y ago
If you want to give Timefold a try locally - it should about twice as fast, still the open source version - try our single Maven or Gradle command on your codebase: https://timefold.ai/upgrade-optaplanner-to-timefold If you
35.
by ge0ffrey 3y ago
Take a look at the two Timefold (continuation/fork of OptaPlanner, open source Apache License) quickstarts for vehicle routing: https://github.com/TimefoldAI/timefold-quickstarts/tree/stab... We regularl
36.
by ge0ffrey 3y ago
Thanks for the kind words about OptaPlanner. We've forked OptaPlanner as Timefold. We don't have a wedding seating example in timefold-quickstarts, yet. Someone did an wedding seating planning implementation 10 years ago: https:&
37.
by ge0ffrey 3y ago
OptaPlanner was forked as Timefold by the team behind it: https://timefold.ai/blog/2023/optaplanner-fork/ We made it twice as fast (by replacing Drools).
38.
OptaPlanner, the open source solver AI, forked as Timefold by its own creator(timefold.ai)
15 points by ge0ffrey 3y ago|4 comments
39.
by ge0ffrey 3y ago
OptaPlanner, the open source planning optimization solver AI, typically used for Vehicle Routing, Maintenance Scheduling and Employee Scheduling, has been forked as Timefold by its own creator.
40.
by ge0ffrey 4y ago
OptaPlanner (Java) or OptaPy (Python) doesn't need any other installations. Just add a dependency in Maven/Gradle (Java) or pip install it (Python).
41.
by ge0ffrey 4y ago
OptaPy (open source, https://www.optapy.org ) solves similar use cases in Python, but using metaheuristics instead of traditional CP techniques, which helps for scaling out.
42.
by ge0ffrey 4y ago
We've done a lot lately to reduce the learning curve for OptaPlanner (open source). Have you seen our quickstarts repo? https://github.com/kiegroup/optaplanner-quickstarts It features various use cases across va
43.
by ge0ffrey 4y ago
Most constraints solvers require math equations based input. If you're more a fan of an Object Orientated Programming and Function Programming coding style, take a look at our solvers: - OptaPlanner (Java, Kotlin, open source, Apache l
44.
by ge0ffrey 5y ago
We did java 8 vs java 11 a few years ago: https://www.optaplanner.org/blog/2019/01/17/HowMuchFasterIsJ... TLDR: using the same GC (*), it's 4% to 16% faster (depending on the GC). But be warned th
45.
by ge0ffrey 5y ago
Of course we accept pull request :) Do start with something small - big changesets are hard to get through the first review. We're on kie.zulipchat.com channel #optaplanner [1] if you want talk about such PR ideas. As for community que
46.
by ge0ffrey 5y ago
Good questions (I am the author). It's complex though. 1) They are not the same benchmark. The Java 15 blog used optaplanner 7.x with optaplanner-examples 7.x, which use scoreDRL. The Java 17 blog used 8.x versions, which use Constrain
47.
by ge0ffrey 5y ago
Here's the script I ran, FWIW: https://gist.github.com/ge0ffrey/34b8a0c2f7b04c2aca7478b0e97...
48.
by ge0ffrey 5y ago
Agreed - but I 'll run the benchmarks anyway for a new blog post. Measuring is knowing. OptaPlanner is best of with Parallel GC (high throughput), but most java processes (REST services etc) are much better off with G1GC (low latency)
49.
by ge0ffrey 5y ago
Thank you for the kind words gavinray :) OptaPlanner is a team and community effort. Credit goes as much to each of them (see team page) as it does to me. And we're standing on the shoulders of giants (other open source projects).
50.
by ge0ffrey 5y ago
> Considering tons of folks are still on Java 8, I would have liked to also see comparison between that and Java 17. We did a comparison of Java 8 and Java 11. And that was a good jump too: https://www.optaplanner.org/blo
51.
Vaccination appointment scheduling is much harder than you'd think(optaplanner.org)
2 points by ge0ffrey 6y ago|0 comments
52.
Vaccination appointment schedule automation and optimization [video](youtube.com)
1 points by ge0ffrey 6y ago|0 comments
53.
by ge0ffrey 6y ago
You're using Clojure with OptaPlanner? That's cool! Any pitfalls with our API's we should know about?
54.
by ge0ffrey 6y ago
OptaPlanner supports continuous planning (see my latest video), which is the ability to use a "sliding planning window". It also supports the use of java.time, which means it supports LocalDateTime, OffsetDateTime, ZonedDateTime,
55.
by ge0ffrey 6y ago
With Quarkus OptaPlanner we're tackling is cloud native / serverless too: https://quarkus.io/guides/optaplanner The -Dnative build compiles your java code natively into an native executable that boots up in m
56.
by ge0ffrey 6y ago
Good question! SHort answer: Local Search is in the AI bible (AI a modern approach by Russell and Norvig), so OptaPlanner is part of AI. Long answer: It depends how old you are. See https://www.optaplanner.org/blog/2017
57.
by ge0ffrey 6y ago
In my experience, seeing OptaPlanner pitted against the other best-of-the-best enterpise-grade solvers, OptaPlanner wins when scaling out - very clearly. Not when scaling down. This is the nature of the Local Search algorithms. The bigger t
58.
by ge0ffrey 6y ago
Are you using ConstraintStreams instead?
59.
by ge0ffrey 6y ago
Yes, our container integration needs to become more streamlined. One of ours first goals is make it very easy to deploy all quickstarts on OpenShift (= Kubernetes) especially the Quarkus ones, by including a docker file and a how-to-deploy
60.
by ge0ffrey 6y ago
It scales better (for example in VRP we had case were OptaPlanner did in 5 minutes what Google OR-Tools did in hours), it can handle fairness and load-balancing constraints (= non-lineair constraints), it supports real-time planning (= chan

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