I write about my everyday life as optimization expert, where I translate business requirements to mathematical formulars, then to software -- and all the way back again.
A drunk-husband-puzzle, and why optimization professionals won't be layed off
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Hello Reader! with wind and rain becoming ever-present, summer has officially given way to autumn. In this episode of Bluebird Briefings I'll give you a little summary of what happened in the world of optimization over the summer of 2025: Major Industry NewsGurobi released the State of Mathematical Optimization 2025 report. It contains results from what's probably the biggest survey among optimization practitioners. The findings are impressive. They attest to the growth of optimization as THE decision-making tool. The report cites optimization as having critical business impact, mainly for cost reductions. It shows that optimization professionals are resilient against layoffs, even in a year where this happens everywhere else. It also documents the growing trend of utilizing Machine Learning and Optimization together. My favorite result is on page 19. Over 60% of respondents plan to increase their use of optimization in the next 12 months. You can request the report for free here. A fun collection of optimization problemsTony Hürlimann updated his book Puzzles and Games — A Mathematical Modeling Approach. If you're looking for fun applications of optimization, this is for you. It's available as a free PDF here: I recommend starting with Problem 2.1, where a "drunk husband" spent $2,000 on wine in a single week. ;) Pair this with an equally tongue-in-cheek take of mine for a twist on bottled beverages. NextMV on Real-World Optimization PracticeNextMV holds a special place in my heart for how they bring testing and deployment to the world of optimization. Now they're extending an open invitation to a tech talk: What to know about practicing operations research and decision science in industry. When: Next Wednesday, October 22 — 8:00 AM PDT / 11:00 AM EDT / 5:00 PM CEST, get your spot here. About the session: Translating academic studies into real-world business practice can be daunting in any discipline, including operations research and decision science. What skills should you have? Where can you get exposed to meaningful experiences? How do you put learning into practice? Bottom line: What do you need to know? Join this session to hear perspectives and conversation on these topics from Ryan O’Neil, Nextmv CTO, and Thiago Serra, Assistant Professor of Business Analytics at the University of Iowa — two OR PhDs with varied experiences in industry, software engineering, and more.
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Bluebird Briefings
I write about my everyday life as optimization expert, where I translate business requirements to mathematical formulars, then to software -- and all the way back again.
Hello Reader! Optimization is one of the most powerful technologies of our time — and yet, it rarely makes headlines. I'm currently returning from the Gurobi Summit 2025 in Vienna. Thus, this newsletter will be a little different: let’s start with three quotes worth highlighting from the event: My personal Top-3 of Quotes “Two years from now, spam will be solved.” – Bill Gates, 2004 This quote was shown at the Summit, alongside many others from world-class figures. And it stuck with me. Not...
Hello Reader! Every Superhero Has an Origin Story For GAMSPy’s machine learning superpowers, that story begins with a package called OMLT. OMLT is short for Optimization and Machine Learning Toolkit. It’s a package that extends Pyomo to integrate machine learning models directly into optimization problems. Because OMLT supports ONNX interoperability, you can take a model trained in TensorFlow, Keras, or PyTorch and embed it into a Pyomo optimization model. It also happens to be the package...
Hello Reader! Here is an intuitive description of the inner workings of 4 different approaches to solving optimization problems: 🔹 Heuristics: Fast & Practical A heuristic is a rule of thumb for decision-making. It doesn’t guarantee the best solution, but it’s often good enough. A strong heuristic has at least one of these qualities: ✅ It finds high-quality solutions quickly. ✅ It delivers decent results with minimal effort. Even if a heuristic fails often, it can still be valuable if it's...