đ To be more creative, visually-explained algorithms, finding the sweet spot
Local Optimum: short, imperfect-yet-useful ideas - Edition #14
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.
Letâs dive in! đȘ
1) đ± To be more creativeâŠ
Apply the 4R framework that I read the other day.
One of those Rs isâŠ
Restrict: To create something, itâs often much better to think âinside a (small) boxâ than to go on about âthinking outside the box.â Although it may sound counterintuitive, constraints are a creatorâs friends.
This is also true for businesses and optimization problems.
In logistics, what you CANâT spend is often more important than what you CAN.
No budget cap? Youâll never weigh ROI.
No driver constraints? Youâll never optimize routes.
No order-mix limit? Youâll never cut warehouse time.
Constraints create optimization problems, what businesses care for, and make us more creative.
(and if you want to know what the other Rs mean, just reply to this email or leave a comment here)
2) đŒïž Algorithms, visually explained
One thing I want to improve is how to visualize ideas.
Itâs powerful.
Our brains process images up to 60,000 times faster than text, so a single graphic can land ideas in milliseconds what paragraphs never will.
Back in the wild, no one texted âlion ahead!â. We saw it and bolted. That split-second of visual processing still rules us today.
Thatâs why diagrams, flowcharts, and annotated sketches turn complex concepts into âaha!â moments.
If you want to see algorithms in practice, take a look here:
3) âïž Finding the sweet spot
When tackling optimization problems, you need to evaluate what to use: an exact or a heuristic approach.
So think aboutâŠ
đŒ The business: will you be able to translate business needs into mathematical equations? Do the requirements change very frequently? Is it a large problem and you need a solution in a few seconds?
đ§đ»âđ» Software development: youâll need to debug and verify solutions, but also consider the programming language youâll use.
đą Optimization: do you care about getting optimal solutions? About getting high-quality solutions in no time?
The choice of which algorithm to choose has many vertices and in most cases it is not usually a direct decision.
You need to understand the problem, the business needs and the skills of the team.
If you want more of this, read the full article:
Symmetry issues in optimization problems (part C)
Next Monday, Iâll share the rest of the article about symmetry issues in optimization problems.
In the first part, I talked about what they are and classical techniques to address them. In the second one, I talked about advanced techniques.
And in Part C, Iâll cover:
đŹ ML-guided techniques to break symmetries
đ Practical ways to dealing with it
I needed to split the article again, it was going to be a huge one!
If youâre dealing with symmetry problems and want to understand ML-guided techniques and useful tips, this will be useful. See you Monday!
And thatâs it for today!
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Have a nice day ahead âïž
Borja.
