Pietro S. Oliveto
机构: Professor of Computer Science, Chair in Algorithms, The University of Sheffield
每年引用次数
引用次数
引用: 2,704
H-指数: 30
I10-指数 : 57
出版物: 139
Analysis of Population-based Evolutionary Algorithms for the
Pietro S. Oliveto
2008
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity
Timo Kötzing , Per Kristian Lehre , Dirk Sudholt , Martin S. Krejca
arXiv: Neural and Evolutionary Computing
1
2016
Hyper-heuristics Can Achieve Optimal Performance for Pseudo-Boolean Optimisation.
Andrei Lissovoi , Pietro S. Oliveto , John Alasdair Warwicker
arXiv: Neural and Evolutionary Computing
3
2018
On the time and space complexity of genetic programming for evolving Boolean conjunctions
Andrei Lissovoi , Pietro S. Oliveto
national conference on artificial intelligence 1363 -1370
4
2018
When Hypermutations and Ageing Enable Artificial Immune Systems to Outperform Evolutionary Algorithms
Pietro S. Oliveto , Dogan Corus , Donya Yazdani
arXiv: Neural and Evolutionary Computing
2018
On the Benefits of Populations on the Exploitation Speed of Standard Steady-State Genetic Algorithms
Pietro S. Oliveto , Dogan Corus
arXiv: Neural and Evolutionary Computing
2019
Simple Hyper-heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes.
Andrei Lissovoi , Pietro S. Oliveto , John Alasdair Warwicker
arXiv: Neural and Evolutionary Computing
1
2018
Erratum: Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation
Pietro S. Oliveto , Carsten Witt
arXiv: Neural and Evolutionary Computing
33
2012
Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms
Pietro S. Oliveto , Dogan Corus
arXiv: Neural and Evolutionary Computing
2
2017
Fast Artificial Immune Systems
Pietro S. Oliveto , Dogan Corus , Donya Yazdani
arXiv: Neural and Evolutionary Computing
4
2018
On the Impact of the Cutoff Time on the Performance of Algorithm Configurators
Dirk Sudholt , Pietro S. Oliveto , George T. Hall
arXiv: Neural and Evolutionary Computing
1
2019
Theoretical Analysis of Stochastic Search Algorithms.
Per Kristian Lehre , Pietro S. Oliveto
Handbook of Heuristics 849 -884
5
2017
How Theoretical Analyses Can Impact Practical Applications of Evolutionary Computation.
Pietro S. Oliveto
IJCCI 5
2019
Analysis of the Performance of Algorithm Configurators for Search Heuristics with Global Mutation Operators
Dirk Sudholt , Pietro Simone Oliveto , George T. Hall
arXiv: Neural and Evolutionary Computing
1
2020
Tutorials at PPSN 2016
Giovanni Squillero , Thomas Bartz-Beielstein , Per Kristian Lehre , Michael G. Epitropakis
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 1012 -1022
2016
Fast Perturbative Algorithm Configurators
Dirk Sudholt , Pietro Simone Oliveto , George T. Hall
arXiv: Neural and Evolutionary Computing
2020
Simple Hyper-heuristics Optimise LeadingOnes in the Best Runtime Achievable Using Randomised Local Search Low-Level Heuristics
Andrei Lissovoi , Pietro S. Oliveto , John Alasdair Warwicker
2018
Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation
P. S. Oliveto , D. Corus , D. Yazdani
arXiv: Neural and Evolutionary Computing
2020
On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials is Best.
Andrei Lissovoi , Pietro S. Oliveto , Carsten Witt , Dogan Corus
arXiv: Neural and Evolutionary Computing
2021
Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation
Pietro Simone Oliveto , Doğan Çörüş , Donya Yazdani
IEEE Transactions on Evolutionary Computation 1 -1
2021