Vehicle Routing Problems are difficult to solve,
especially at scale with real-world constraints.
Both for humans and software.
In this video, I explain why VRPs are challenging,
what technology solutions exist
and how you can solve them easily in practice.
www.youtube.com/watch?v=Lcdw...
Sunday evening, a long-lost friend messaged me:
"I wrote a Hockey Training scheduling application in weekend with Timefold and Claude."
In a weekend.
It's an amazing age we live in!
He even documented the whole thing.
Here's how he did it:
medium.com/@bavo.bruyla...
At the Dublin Java User Group, Tom will solve Santa's scheduling and routing optimization problems with Timefold Solver (our open source solver previously known as OptaPlanner) on Tue 27 jan:
www.meetup.com/dublinjavaus...
How fast is Java 25?
timefold.ai/blog/how-fas...
by @tomcools.be
We did it!
Our shift scheduling API now supports over 100 business constraints.
Whether your dataset is using 1 or 100 constraints, with 50 or 50'000 employees, with 200 or 200'000 shifts, it delivers a near-optimal solution in minutes or less.
app.timefold.ai
🚀 Our new API for Pickup and Delivery Routing is out! 🚀
It optimizes in-route pickup and delivery of people or packages.
For example:
- Non-emergency medical transport to bring patients to the hospital
- School bus optimization
- Food delivery
- Parcel delivery
app.timefold.ai/models/picku...
Looking forward to it!
The Sunk Cost Fallacy
After you've worked weeks on an improvement that turns out as not much of an improvement...
... this Pull Request appears ...
Mario Fusco @ #devoxx
"Why can't you just have ChatGPT generate a schedule for you?"
In this podcast, Mackenzie Jackson and I didn't just drink sake, we also covered complex scheduling and routing with AI and founding a company.
Watch it here:
www.youtube.com/watch?v=58CM...
"Why haven't they fixed this yet?" @smarks.bsky.social and Maurice talking about ConcurrentException etc in #java at #devoxx
Great talk, but when they cover Vector and Hashtable, I can't stop and think:
"Why haven't they deprecated this yet?"
#Devoxx talk trial run in front of a "live" audience. 😅 If you are at the conference, do say hello when you see me. 😊
An Open Source project needs a real-time chat for the community to come together.
So we created a Discord chat for Timefold Solerv.
To ask questions.
To discuss ideas.
Or to figure out how to hack the solver to run your crazy experiment.
Join us:
discord.gg/976RcEVVHW
In the Optimization4All podcast, Cristina Radu and I talked about Operations Research, starting a company and Timefold.
Watch the podcast:
www.youtube.com/watch?v=rrLb...
Today is the day... 🤩☕️🔥 #Java
This way he won't be to install himself in a train seat.
If it takes 10 000 hours to master a craft,
what do you get for 10 000 commits?
Timefold Solver, our Open Source solver for complex scheduling and routing problems, just reached 10 000 commits on GitHub:
github.com/TimefoldAI/t...
Can the optimal solution for a Traveling Salesman Problem (TSP) have crossing paths?
No, it cannot.
Because of the Triangle Inequality principle.
But in reality, it can.
Because there's road infrastructure: highways, one-way streets, etc.
In the real-world, solution optimality is rarely obvious.
A great plan is worthless if you can't explain why.
For the operators to trust your software, they need more than a button to "Schedule with AI" that generates the optimized schedule for their employees.
They need explainability. Learn how by @tomcools.be :
timefold.ai/blog/explain...
Vehicle Routing Problems in production:
When research meets reality.
Our webinar yesterday covered:
- Maps integration
- Time calculation
- Hard constraints in reality
- Multi-objective optimization
- Real-time planning
See the recording:
www.youtube.com/watch?v=l12G...
That moment when your backend algorithms optimize a vehicle routing dataset with thousands of visits...
... and your frontend turns into a piece of modern art.
Doh. I meant float instead of int.
This is what happens if you use floating point numbers (int, double in #Java) for financial data.
Use decimal numbers (BigDecimal in Java) instead.
Where does your enterprise stand on the scheduling maturity ladder?
Are your resources scheduled manually?
With or without constraint verification?
Or automatically?
With or without optimization?
Discover the 4 Levels of Scheduling:
timefold.ai/blog/the-4-l...
Can LLMs solve scheduling or routing problems?
Can GenAI help companies save millions of dollars by optimizing Vehicle Routing, Shift Rostering or Job Scheduling to increase productivity and retention?
@tomcools.be and I tried it out:
www.youtube.com/watch?v=m12A...
#VRP #AI #PlanningAI #DevoxxFr
Our team has just released Declarative Shadow Variables (Preview) with our #opensource Timefold Solver 🤩 . It's easier than ever to calculate shadow variables.
As a preview feature, the API is not yet set in stone and we are actively looking for feedback. 👍
github.com/TimefoldAI/t...
Most publications of the Vehicle Routing Problem only cover the tip of the iceberg.
Benchmarks and academic papers typically only handle vehicle capacity (CVRP) and time windows (VRPTW)
But production deployments also need to deal with many other requirements.
#OperationsResearch #PlanningAI #AI
Discover how AI can step up when LLMs fall short in scheduling. Join @tomcools.be and dive into Timefold, a Java-based AI solver that optimises schedules using advanced math. See live demos and enhance your problem-solving skills!
Session details @ buff.ly/TePAVmY
But it doesn't stop there.
We're working on two exciting, big new features for Timefold Solver. Both are game changers to tackle real-world Operations Research problems.
More on that later. Stay tuned!
Timefold Solver is still the foundation of everything we do at Timefold, so we continue to invest in it, with our dedicated solver team.
Since we forked from OptaPlanner, we've made it faster, easier to use and more flexible to deal with real-world requirements, such fairness and resource limits.
Our Open Source solver now has a dedicated home: solver.timefold.ai
It's a place for the Timefold Solver community,
with everything you need to build a solution
for any planning, scheduling or routing optimization problem.
Is there anything missing that you would like to see on solver.timefold.ai?
