📈 There’s one thing you don’t need, a new challenge, the power of competitions

Local Optimum: short, imperfect-yet-useful ideas - Edition #12

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! 🪂

1) 🙅 There’s one thing you don’t need

Unlike in your thesis research, real-world optimization projects rarely require a formal proof of optimality:

• It’s expensive in terms of developing and running times

• Businesses don’t care if you got the optimality or got behind by 1%

• There are a lot of stochastic processes that make it impossible to guarantee optimality

So next time, ask yourself if a good enough solution will do the trick.

2) 🎯 A new challenge

Competitions can be a good place to challenge yourself to learn new concepts or force yourself to give a software solution in no time.

And I just found a new optimization competition in Colombia during this month.

Those are the things we need more of!

3) 🏆 The power of competitions

I’ve seen many competitions in Machine Learning in specific places like Kaggle or AIcrowd.

One of the best things they do is to gather lots of people around a topic, nurturing a community of engaged developers.

They do it through:

• Democratizing problem-solving

• Fostering rapid knowledge exchange

• Bridging the gap between theoretical research and actionable solutions

However, I haven’t seen the same happening in Operations Research.

A centralized platform for competitions in OR would help a lot, really, as today you need to be in touch with all the organizations that creates a challenge (like ASOCIO in Colombia as I said in the previous section).

That’s why I talked about the power of competitions in OR:

📈 #56 The power of competitions in Operations Research

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Symmetry problems in optimization…

Are draining your brain.

When you can assign the same resource to several tasks, and it happens to several resources at the same time, you most probably are facing a symmetry.

They’re a pain as they make your problem more complex than usual. I lived it in my skin.

Next Monday, I’ll share the third part of the 6-part series titled Where did the time go?, where I address several topics around tractability issues in optimization problems.

I’ll cover:

🧱 What symmetry means in optimization
🚨 How it can ruin solver performance
🛠 Practical ways to dealing with it

If you’re facing symmetry problems, this will be useful. See you Monday!

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And that’s it for today!

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Have a nice day ahead ☀️

Borja.