ETD

Digital archive of theses discussed at the University of Pisa

 

Thesis etd-09042017-113548


Thesis type
Tesi di laurea magistrale
Author
IOMMAZZO, GABRIELE
URN
etd-09042017-113548
Thesis title
Combining Machine Learning and Mathematical Optimization techniques to tackle IBM ILOG CPLEX automatic configuration on Hydro Unit Commitment problems
Department
INFORMATICA
Course of study
INFORMATICA PER L'ECONOMIA E PER L'AZIENDA (BUSINESS INFORMATICS)
Supervisors
relatore Prof. Frangioni, Antonio
Keywords
  • machine learning
  • mathematical optimization
  • svr
  • hydro unit commitment
  • cplex
Graduation session start date
06/10/2017
Availability
Full
Summary
This work want to build an approach that can select the best algorithmic parameters of the optimization solver IBM ILOG CPLEX, for solving instances of a specific Hydro Unit Commitment problem, This goal is achieved by mixing Machine Learning and Mathematical optimization methods and algorithms.
File