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Pietro S Oliveto

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Evolutionary Computation|September 26, 2015
Editorial for the Special Issue on Theory of Evolutionary Algorithms 2014Pietro S Oliveto, Andrew M Sutton
Evolutionary Computation|May 24, 2019
Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes<sup></sup>Andrei Lissovoi, Pietro S Oliveto, John Alasdair Warwicker
Evolutionary Computation|November 18, 2009
Analysis of diversity-preserving mechanisms for global explorationTobias Friedrich, Pietro S Oliveto, Dirk Sudholt, et al.
Algorithmica|April 19, 2019
How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms ElitismPietro S Oliveto, Tiago Paixão, Jorge Pérez Heredia, et al.
Algorithmica|February 28, 2020
On Easiest Functions for Mutation Operators in Bio-Inspired OptimisationDogan Corus, Jun He, Thomas Jansen, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Evolutionary Computation|September 26, 2015
Editorial for the Special Issue on Theory of Evolutionary Algorithms 2014Pietro S Oliveto, Andrew M Sutton
Evolutionary Computation|May 24, 2019
Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes<sup></sup>Andrei Lissovoi, Pietro S Oliveto, John Alasdair Warwicker
Evolutionary Computation|November 18, 2009
Analysis of diversity-preserving mechanisms for global explorationTobias Friedrich, Pietro S Oliveto, Dirk Sudholt, et al.
Algorithmica|April 19, 2019
How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms ElitismPietro S Oliveto, Tiago Paixão, Jorge Pérez Heredia, et al.
Algorithmica|February 28, 2020
On Easiest Functions for Mutation Operators in Bio-Inspired OptimisationDogan Corus, Jun He, Thomas Jansen, et al.
Pageof 1