Python, ottimizzazione numerica, algoritmi genetici

of Davide Rizzo

Mathematical optimization means to face a complex decision and find the solution which reduces the cost to a minimum, which satisfies my customers the most, which maximizes my system efficiency.


Python entered by force in the world of numerical analisys years ago and opens to users enormous potentials to resolve problems while looking for the optimum.

In this introduction I'll show the main approaches to numerical optimization problems, making use of tools that are already known in scientific world as SciPy and PyMathProg, and I'll present some application examples.
I'll explain genetic algorithms as a research instrument for the optimum according to an approach that is different compared to the traditional numeric ones, easy to handle thanks to Python (PyGene) and suitable for a new class of application problems from which I''ll take some significant examples.
 

pycon4 - Sat 08 may / 16:00 in the track Diffondere Python.

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Slide (PDF Document) — 1.3 MB
Language
IT
Duration
90 minutes