Introduction to Metaheuristics (4/9). Classification criteria for metaheuristics
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- Опубліковано 10 лют 2025
- Playlist at • Introduction to Metahe...
Classes for the Degree of Industrial Management Engineering at the University of Burgos.
To see these videos in Spanish, please go to • Introducción a las téc...
the video series is awesome... it really helped me out with the basics a lot!! thanks a lot sir!
Please come back with the detailed course on metaheuristics! I'm sure it would be a great value to us... Thanks
3:58 Iterative methods (e.g., Newton Rhapson) progressively improve an initial guess until convergence. Also, i think the slide should say genetic (not "greedy").
I do not agree. It can say greedy (or constructive, or successive augmentation algorithm) and should definitely not say genetic. Genetic algorithms work in a completely different way. You can check this reading the book I cite in the slide, i.e. Talbi (2009). Page 26 of the book for a definition of greedy and section 3.2.1 (p. 201) to learn how genetic algorithms work.
@LuisRIzquierdo To clarify I meant genetic as in GP not GA. (GP varies chromosome size)
Re Talib 09 pg 21: "in greedy or constructive algorithms ^also referred to as successive augmentation algorithms" seems to conflate greediness (i.e., exploitation, e.g., gradient descent) with a totally different concept. In optimization, there's no such thing as an empty solution in N-space nor is it possible to evaluate an incomplete solution-vector, e.g. 10D Schwefel with only 1 variable specified.
This is such a great video. Especially the ending slide.
thank u Phil Dunphy
That is such an amazing video, and it is especially helpful.
Glad you found it useful!!
Thank you
Hi Luis, It will be really helpful if you provide your presentation slides. Where can I get it?
The link is on the description of the playlist: www.dropbox.com/s/zl0kfxqmmmlvhss/Introduction%20to%20metaheuristics.pdf?dl=0