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Newsletter 4: A big Speed Upgrade for Timefold - Our First Customer Story and AMA!
Unlock unprecedented speed with Timefold's latest update! Essential for OptaPlanner and pre-1.8.0 users – upgrade now for instant gains
Bye Bye dummy vehicles, hello speed upgrade!
TL;DR: OptaPlanner and pre-1.8.0 Timefold users should upgrade for yet another significant performance boost.
Building on last year’s massive speed gains, we’re shifting to a higher gear.
Timefold 1.8.0 introduces support for planning list variables with unassigned values (nullable), enhancing scalability and efficiency.
Why should you care? It represents a big performance gain, especially when your operations doesn’t have enough resources to assign all necessary tasks to.
Your planning model benefits from this upgrade if it:
Encounters Overconstrained Planning: struggling to assign all necessary tasks due to a shortage of resources.
Implements the @PlanningListVariable annotation for managing planning list variables.
Uses Multi-Resource Planning: Ideal for scenarios requiring multiple resources, like several vehicles or technicians at one location.
Impact of this upgrade:
OptaPlanner and pre-1.8.0: Models used "virtual vehicles" for tasks, which didn't scale well in multi-resource scenarios.
Now, with 1.8.0: Introducing nullable planning list variables significantly improves scalability, showing remarkable performance in datasets with multi-resource visits.
Ok, what does the data say?
In the graph below we look at the impact on a Field Service Routing model with varying data set sizes. We look at the score calculation speed and benchmark versus the baseline, before Timefold 1.8.0 and after Timefold 1.8.0
What is important for scalability is not the absolute value of the bar, but the speed with which it decreases with larger datasets.
The comparison of performance across different dataset sizes (from 60 to over 1200 visits) shows that nullable planning list variables maintain consistent performance, unlike virtual values that degrade with larger datasets.
This update is crucial for anyone dealing with overconstrained planning and multi-resource tasks, promising substantial scalability and efficiency improvements. Upgrade today
Case Study
Ecoprogram Flotte, an Italian leader in automotive logistics, needed a solution to optimize its transport planning. With Timefold, the company managed to build the best operational change ever for the company: a platform that makes vehicle deliveries and pick-ups more efficient and environmentally friendly.
Challenge:
Streamlining the logistics to prepare and deliver 245,000 new cars to customers, while also managing the pickup of their used vehicles.
This requires custom route planning for each driver, factoring in availability, residence, and more.
About Ecoprogram Flotte:
- €258 million revenue (2024)
- 245000 car deliveries (2024)
- 850 employees, 300 drivers
Collaborates with international groups such as Arval, Gruppo Bnp Paribas, ALD Automotive, Leasys, Unipol Rental, LeasePlan.
What Ecoprogram Flotte says about Timefold:
“The Timefold platform is better than anything we have ever seen in the history of the company. Moreover, it fits in perfectly with our company’s sustainable ambitions.”
“The number of staff in the planning team decreased from five to one. “We still see a big potential to further improve our planning and service delivery. This software enables us to stand out in our industry.”
Blog
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This article is focused on a more advanced pinning application for the Vehicle Routing Problem.
Release notes
Timefold Solver Community Edition 1.8.0. full release notes
Spring is in the air, and so is another release of Timefold solver. This release is a significant leap forward, not just for our Community Edition users but for our Enterprise Edition clients as well, with each edition packed with features designed to supercharge your operations.
For our Community Edition, we have prepared the following features:
List variables now allow for unassigned values. Read the beginning of this mail for more information.
Spring Boot users among you can now easily generate native images, as was already possible for Quarkus.
ConstraintVerifier can now test for justifications and indictments, allowing you to write tests that will give you even more confidence in your constraints than was possible before.
We have exposed new metrics that allow you to better monitor the currently running solver(s).
And last but not least, we've brought the usual bugfixes and dependency upgrades.
Exclusive Features for Enterprise Edition 1.8.0: Beyond the enhancements of the Community Edition, our Enterprise Edition users can access additional powerful features designed to significantly boost efficiency and performance.
Automatic node sharing. Use cases with a large number of complex constraints may run as much as 30 % faster without any changes to your code.
Nearby Selection can now be enabled with a single switch in your configuration, as opposed to the cumbersome configuration of old. If you're still not using Nearby Selection for your large routing problems, you're missing out on cost savings coming from significantly improved solutions!
Going forward, we will be publishing an Upgrade Recipe to let you know of any things you may or may not run into when upgrading to the latest version of Timefold Solver. It's a good read!
Here you can find all previous releases of Timefold Solver.
