Best practices in measuring energy consumption in
population-based metaheuristics
JJ Merelo, Cecilia Merelo-Molina
Universidad de Granada, Zenzorrito
Modern Taurokathapsia
We need to tame the bull of energy consumption in
EAs
Meet the Brave New Algorithm
Literature-inspired metaphor
Stratified population evolutionary algorithm
α caste → with itself, crossover +
mutation
β only with α → crossover +
mutation
γ, δ, ε → only mutation; γ →
hillclimbing
It's only fitting that we use Greek letters
Crossover was invented in Crete
After a couple of failed attempts
☝️Take it easy
⏱️ Decrease sampling frequency
✌️ Improve little by little
📏 But always measure after trying to
improve
Ⅲ Adjust your perception of reality
to find out what's happened
Baseline shouldn't move too much...
But it does
🎯 Ⅳ Localize your measures
🔗 Don't separate baseline and workload
measurements
We can compare now!
Conclusions
Taming the energy bull requires
measuring it first
The Brave New Algorithm provides an
interesting framework for applying it to evolutionary
algorithms
Follow best practices to make the
measured workload stand out
Let literature
and Greek history and philosophy
be your guide
Σας ευχαριστώ πολύ!