📈 Did Dijkstra just get dethroned? → The paper + 7 more OR finds
Search space: your dose of OR discoveries
Hey, Borja here! 👋
I'm trying something new today.
Instead of letting all the interesting research and tools I discover each week disappear into my bookmark graveyard, I'm sharing the ones that made me pause and think this is clever or I need to remember this.
Consider it your weekly dose of OR discoveries without the time investment of finding them yourself.
Let me know if this hits the mark: your feedback will determine if this becomes a regular thing.
🏎 How to find the shortest path, faster: Dijkstra’s algorithm dominated this problem, but now researchers from the Max Planck Institute for Informatics broke the barrier. If you want to read a free version of the paper, here.
⏳ For algorithms, a little memory outweights a lot of time: Ryan Williams’ 2025 proof shows that any algorithm taking T steps can be simulated with roughly √T memory, breaking a 50-year deadlock and proving that a sliver of space can beat oceans of time.
🎢 Introduction to Minimum Cost Flow Problem: what it is, and how to solve it with Python, by Reinhard Sellmair.
🧬 LLMs meet Evolutionary Algorithms: a nice summary from Eric Bonabeau of how both fields support each other in several ways, via Manuel López-Ibáñez.
🐍 pyOptInterface, a well-written and fast modeling framework, but what can it do? By Richard Oberdieck.
🎆 A parallel implementation in Java of Adaptive Large Neighborhood Search (jPALNS), by Nils Beckman.
🗺 spopt: a spatial optimization framework in Python by PySal team, lead by James Gaboardi, via Kyle Walker.
🚢 DecisionOps, or how to productionize OR models: a talk by ECCO’s Lead Data Scientist, Matthias Als.
Found something I should see? Send it my way and I’ll credit you next week.
In the meantime…
Let’s keep optimizing,
Borja.
