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Comparing optimizers on a unit commitment problem

Vincent Berthier 1, 2
1 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : This paper compares several black-box optimization algorithms on a unit commitment problem. Compared to existing testbeds, this one provides several scales, is real-world, and none of the compared algorithms were created by the author of the testbed. Differential Evolution basically performs best overall, though not for all test cases.
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Contributor : Vincent Berthier <>
Submitted on : Thursday, October 15, 2015 - 7:10:33 AM
Last modification on : Friday, April 30, 2021 - 9:56:24 AM
Long-term archiving on: : Thursday, April 27, 2017 - 4:27:19 AM


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  • HAL Id : hal-01215804, version 1


Vincent Berthier. Comparing optimizers on a unit commitment problem. Artificial Evolution (EA2015), Oct 2015, Lyon, France. ⟨hal-01215804⟩



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