📈 No electricity in Spain, I feel proud, Fast convex optimization, and Small bakery but big optimization problem
Local Optimum: short, imperfect-yet-useful ideas - Edition #7
Welcome to a new edition of Local Optimum: a short, imperfect-yet-useful collection of ideas related to optimization, decision-making, and applied Operations Research.
Let’s dive in! 🪂
0) ⚡️ No electricity in Spain
Last Monday, Spain blacked out…
And I took advantage of the situation and ate a lot of ice cream, just in case it melted!
It also reminded me of some optimization problems that may be of help in extreme situation.
(click on the image below to go to the post)
1) 🏆 I feel proud
When someone cites you, it’s amazing.
When someone gives you credit, it’s awesome.
But when someone repurposes your content as a way of teaching, it’s an incredible feeling.
That happened the other day, and I feel very proud of that.
A professor from Facultad de Ciencias Empresariales UTP, in Colombia, repurposed and gave me credit for a post I created time ago, and I needed to share that today.
Not only that, she repeated it after some days with different content.
Thank you for that, prof. Eliana :-)
2) ⏱️ Fast convex optimization
Two Thursdays ago I talked you about using SAT solving for Quantum Computing.
Today’s the turn for using Quantum Computing contributing to convex optimization.
The paper Fast Convex Optimization with Quantum Gradient Methods shows that quantum algorithms without gradient access can match the convergence of classical gradient-descent methods, which do assume gradient access.
In the derivative-free setting, this translates to an exponential speedup in terms of the dimension.
And it’s especially useful for solving Linear Programming problems at scale.
3) 🥐 Small bakery, big optimization problem
Small business.
Small oven.
Small product line.
So… Why is this a big problem?
Imagine you're a baker with one oven, two products, and a desire to make the most money. Sounds simple, right?
But when your cookie limit is fractional, your cakes take up 7 units of oven space, and your goal is to optimize revenue, you enter the world of linear programming.
Easy enough until you say:
I can’t sell half a cake.
Suddenly, you’re in a very different world: Integer Programming.
Solutions shift. Revenues change. Complexity explodes.
What seemed like a simple morning problem now mirrors the challenges of airline scheduling, delivery routing, or staff assignment.
All from a bakery on a Friday.
That’s the beauty of Operations Research: small problems are never just small.
You can read the full article here:
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Have a nice day ahead ☀️
Borja.
