A decade of OptaPlanner

10 years ago, I started a little project during my vacation.
Nothing serious. Just a hobby, it wouldn’t be big and professional.
Another contraption in my long list of side projects in an attempt to build something cool.
Today, that same project is now the leading Open Source constraint satisfaction solver in Java: OptaPlanner.
It is used across the world to create better logistic schedules, such as employee rosters,
vehicle routes and cloud distributions.

How did my project become successful? What did I do right? What did I do wrong?

Proving a point

After graduating in 2003, I worked 2 years as a Java consultant and then took a job as an academic researcher on multi-agent systems.
Those were going to change the world. They didn’t.
One of my colleagues was working on optimizing a nurse rostering problem and presented his approach to our research group.
His solution applied Tabu Search (an optimization algorithm invented in the ’80s).
It worked well.
However, he had spent a lot of time and energy to manually implement the incremental delta calculation for each constraint in the fitness function.
Writing that code is difficult, time consuming and error prone, but absolutely required to get good results when scaling out.

The year before, I had seen Mark Proctor’s presentation at JavaPolis (now called DevoxxBE),
explaining the Drools rule engine and the RETE algorithm.
A stateful rule engine tracks changes so it only has to check the rules that might be affected by those changes.

Light bulb.
What if we use Tabu Search but implement the fitness function in a rule engine?
I proposed it to the group. They laughed at me.
Of course, at the time I had zero experience with optimization algorithms.

Talk is cheap, so I implemented a proof of concept during my 2006 summer holiday
to schedule a simplistic lesson scheduling problem.
I called it Taseree. That’s an abbreviation for Tabu Search Rule Engine Evaluation.
Later that year, I added 2 more examples (N Queens and TTP) and open sourced it on SourceForge.

Nobody ever used Taseree, let alone deployed it in a production environment.
Turns out if you don’t release it, nobody uses it.

Research competitions

This is probably where the story would have ended – just like my dozens of other hobby projects of that period.
But I heard about a few academic research competitions: given an optimization problem, find the best solution for each dataset in 5 minutes.
So I entered the International Timetabling Competition 2007 to solve an exam rostering problem.
I finished 4th. Out of maybe two hundred contenders.

So I must have been doing something right. But I did a lot of things wrong, too.
The winner had also open sourced his implementation and when we started discussing and comparing our implementation,
we learned a lot from each other.
It turns out there are many ways to skin a cat and there are far more ways to implement Tabu Search.
So I started implementing alternative algorithms. That made me (and later Lukáš) write the benchmarker toolkit, to compare those algorithms statistically.
All just to rank better in the next competition. It takes an hour to understand these algorithms, but 10 000 hours to master them.

Motivation is key. Find a way to motivate yourself to build the next feature, especially in the absence of a paycheck.
And avoid creating technical debt: nothing is more demotivating in a hobby project.

Another advantage was that each competition results in a new example.
So I had to eat my own dog food.
I ended up doing a lot of framework changes to make it easier for me to implement those use cases.
This is an important, old rule in project management: Those that create the pain, should feel the pain.
Writing examples against a predefined set of requirements, is a great way to feel the pain.

No man is an island

Around the same time I reached out to the Drools team,
simply by joining their IRC channel.
I started talking. Networking really. I learned what I needed to learn.
By September 2007, Mark invited me to make Taseree a subproject of Drools and we called it Drools Solver.
So I cleaned up the code, removed the spring-core dependency (which I had dragged in for no good reason except to have an XML configuration)
and wrote the first chapter of the reference manual. It got released as part of Drools 5.0.

By December 2007, I gave my first presentation about Drools Solver’s exam rostering example
at a late evening Bird of a Feather session at JavaPolis, for about 20 developers.
I had prepared my text word by word in advance and read it out aloud.
Not my best moment. But they did seemed to like my demo though.
I am not a natural born presenter,
but I soon realized that great slides and polished demos can make up for that.
These days I can step into a room – unprepared – and talk for 5 days without showing the same slide or demo twice.
Presenting skills can be acquired.

In 2008, I heard about the first production use of Drools Solver.
A consultant had seen my presentation at JavaPolis and he used it for an employee rostering problem.
He liked it. So I expected him to tell the world about it. He didn’t. He had already moved on to his next project.
To get people to use my project, they need to know it first.
I needed to toot my own horn.
So I wrote a few articles about Drools Solver, published them to a few Java news sites, recorded a video even and even got a twitter account.


Up to 2008, I had enough spare time in my personal life to dedicate several hours per week on Drools Solver.
But then I bought an old house with my girlfriend (who’s now my wonderful wife) and I spent most of my free time renovating it.
This naturally stalled development, often for months at a time.

Meanwhile, I learned more about other, similar projects. And they seemed to have more people working on them.
And they had sales people. It was a race and my project was falling behind.
I needed to find a way to get paid to work on it. A way to make my hobby my job.
No matter how good the code is technically, without a proper business model behind it, an Open Source project is unsustainable.

During this tough period, I regularly considered giving up my Open Source project a few times.
Somehow, I couldn’t. I just soldiered on. And in the end, it all worked out well.

Ironically, this was also the period when the project became successful:
downloads took off, the forum became vibrant, I got to talk at more conferences and the first Pull Request arrived.
Due to its success, more bugs surfaced – so I heavily invested in unit tests and integration tests.
By the end of 2009 I also renamed the project to Drools Planner.

Luckily Red Hat – sponsor of the Drools project – had noticed my steady stream of contributions.
They originally hired me to work on Drools itself, but as of January 2013 they assigned me full time on Planner.
Red Hat pays the wage of the core engineers of many Open Source projects
and makes a business from selling support subscriptions and consultancy for those projects.

Productization: going enterprise

By the end of 2012, my little project had already grown quite big: it had a high test coverage with unit, integration and stress tests,
a complete reference manual, demonstrable examples, javadocs and a growing community.
But there were also many services missing before a Fortune 500 company would consider using it in mission critical software.
Technical excellence alone doesn’t suffice.

Red Hat doesn’t just employ the core engineers of an open source project, such as Drools or OptaPlanner.
It also builds out a dedicated QA team, support team, consultancy team, security team and productized build/documentation team.
This enables customers to deploy our Open Source software in large scale production cases confidently.
In 2013, we started this process, called productization.

I was no longer alone on the project. Quality Assurance, Product Management and our productization build/document team got involved to strengthen it.
Our QA engineers double checked the code, increased test coverage, added performance regression tests,
certified it on a lot of environments (including Windows, IBM JDK, OSGi and other notorious technologies) and guess what – they found bugs (and still do on occasion).
Meanwhile our Product Manager helped organizationally.
We talked to customers and helped complex use cases succeed: all very satisfying.
And I got to travel to interesting places around the globe, such as San Francisco, Boston, Buenos Aires, London, Paris and Tokyo.

Meanwhile, our project also graduated from the Drools project to become a top-level project.
So we had to rename the project again, one last time (I promise), to OptaPlanner.
Changing a project’s name is a delicate operation: it always reduces the mind share. Try to avoid it.
We also created the optaplanner.org website as a one stop location for all information. Centralization of information is essential to pull the community together.

In March 2014, we released the first version with tech preview support from Red Hat, as part of the BRMS subscription.
And by March 2015, we upgraded it to full enterprise support.
Sales took off. So earlier this year, we could hire a core engineer to develop OptaPlanner Workbench.
Meanwhile, all our code is still Open Source, under the Apache License
and thousands of projects use it. A win-win situation.

The future is bright.

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