Pietro S. Oliveto

ORCID

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 70

Top Venues

Publications

Benjamin Doerr, Andrei Lissovoi, Pietro S. Oliveto
(1+1) Genetic Programming With Functionally Complete Instruction Sets Can Evolve Boolean Conjunctions and Disjunctions with Arbitrarily Small Error. CoRR (2023)
Benjamin Doerr, Andrei Lissovoi, Pietro S. Oliveto
(1+1) genetic programming with functionally complete instruction sets can evolve Boolean conjunctions and disjunctions with arbitrarily small error. Artif. Intell. 319 (2023)
Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
When move acceptance selection hyper-heuristics outperform Metropolis and elitist evolutionary algorithms and when not. Artif. Intell. 314 (2023)
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
On the impact of the performance metric on efficient algorithm configuration. Artif. Intell. 303 (2022)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of population-based evolutionary algorithms. GECCO Companion (2022)
Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
Tight Bounds on the Expected Runtime of a Standard Steady State Genetic Algorithm. Algorithmica 84 (6) (2022)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of evolutionary algorithms: basic introduction. GECCO Companion (2021)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Fast Immune System-Inspired Hypermutation Operators for Combinatorial Optimization. IEEE Trans. Evol. Comput. 25 (5) (2021)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of population-based evolutionary algorithms. GECCO Companion (2021)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Automatic adaptation of hypermutation rates for multimodal optimisation. FOGA (2021)
Dogan Corus, Andrei Lissovoi, Pietro S. Oliveto, Carsten Witt
On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials is Best. CoRR (2021)
Dogan Corus, Andrei Lissovoi, Pietro S. Oliveto, Carsten Witt
On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials Is Best. ACM Trans. Evol. Learn. Optim. 1 (1) (2021)
Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
A tight lower bound on the expected runtime of standard steady state genetic algorithms. GECCO (2020)
Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
. Evol. Comput. 28 (3) (2020)
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
Analysis of the Performance of Algorithm Configurators for Search Heuristics with Global Mutation Operators. CoRR (2020)
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
Fast Perturbative Algorithm Configurators. PPSN (1) (2020)
Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
How the Duration of the Learning Period Affects the Performance of Random Gradient Selection Hyper-Heuristics. AAAI (2020)
Michael Foster, Matthew Hughes, George O'Brien, Pietro S. Oliveto, James Pyle, Dirk Sudholt, James Williams
Do sophisticated evolutionary algorithms perform better than simple ones? GECCO (2020)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation. CoRR (2020)
Pietro S. Oliveto, Anne Auger, Francisco Chicano, Carlos M. Fonseca
Guest Editorial Special Issue on Theoretical Foundations of Evolutionary Computation. IEEE Trans. Evol. Comput. 24 (6) (2020)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2020. GECCO Companion (2020)
Pietro S. Oliveto, Andrew M. Sutton
Theory of evolutionary computation - Special Issue Editorial. Theor. Comput. Sci. 832 (2020)
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
Analysis of the performance of algorithm configurators for search heuristics with global mutation operators. GECCO (2020)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms. Theor. Comput. Sci. 832 (2020)
Dogan Corus, Pietro S. Oliveto
On the Benefits of Populations for the Exploitation Speed of Standard Steady-State Genetic Algorithms. Algorithmica 82 (12) (2020)
Dogan Corus, Pietro S. Oliveto
On the benefits of populations for the exploitation speed of standard steady-state genetic algorithms. GECCO (2019)
Benjamin Doerr, Andrei Lissovoi, Pietro S. Oliveto
Evolving Boolean Functions with Conjunctions and Disjunctions via Genetic Programming. CoRR (2019)
Pietro S. Oliveto, Dirk Sudholt, Christine Zarges
On the benefits and risks of using fitness sharing for multimodal optimisation. Theor. Comput. Sci. 773 (2019)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of evolutionary algorithms: basic introduction: introductory tutorial at GECCO 2019. GECCO (Companion) (2019)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Artificial immune systems can find arbitrarily good approximations for the NP-hard number partitioning problem. Artif. Intell. 274 (2019)
Pietro S. Oliveto
How Theoretical Analyses Can Impact Practical Applications of Evolutionary Computation. IJCCI (2019)
Samadhi Nallaperuma, Pietro S. Oliveto, Jorge Pérez Heredia, Dirk Sudholt
On the Analysis of Trajectory-Based Search Algorithms: When is it Beneficial to Reject Improvements? Algorithmica 81 (2) (2019)
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
On the impact of the cutoff time on the performance of algorithm configurators. GECCO (2019)
Dogan Corus, Pietro S. Oliveto
On the Benefits of Populations on the Exploitation Speed of Standard Steady-State Genetic Algorithms. CoRR (2019)
Benjamin Doerr, Andrei Lissovoi, Pietro S. Oliveto
Evolving boolean functions with conjunctions and disjunctions via genetic programming. GECCO (2019)
George T. Hall, Pietro S. Oliveto, Dirk Sudholt
On the Impact of the Cutoff Time on the Performance of Algorithm Configurators. CoRR (2019)
Andrei Lissovoi, Pietro S. Oliveto
On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions. J. Artif. Intell. Res. 66 (2019)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
On inversely proportional hypermutations with mutation potential. GECCO (2019)
Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation. AAAI (2019)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
On Inversely Proportional Hypermutations with Mutation Potential. CoRR (2019)
Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton
Escaping Local Optima Using Crossover With Emergent Diversity. IEEE Trans. Evol. Comput. 22 (3) (2018)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Fast Artificial Immune Systems. CoRR (2018)
Andrei Lissovoi, Pietro S. Oliveto
On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions. AAAI (2018)
Dogan Corus, Pietro S. Oliveto
Standard Steady State Genetic Algorithms Can Hillclimb Faster Than Mutation-Only Evolutionary Algorithms. IEEE Trans. Evol. Comput. 22 (5) (2018)
Dogan Corus, Pietro S. Oliveto
Standard steady state genetic algorithms can hillclimb faster than evolutionary algorithms using standard bit mutation. GECCO (Companion) (2018)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of evolutionary algorithms: basic introduction. GECCO (Companion) (2018)
Benjamin Doerr, Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
On the runtime analysis of selection hyper-heuristics with adaptive learning periods. GECCO (2018)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem. CoRR (2018)
Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
Hyper-heuristics Can Achieve Optimal Performance for Pseudo-Boolean Optimisation. CoRR (2018)
Pietro S. Oliveto, Tiago Paixão, Jorge Pérez Heredia, Dirk Sudholt, Barbora Trubenová
How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms Elitism. Algorithmica 80 (5) (2018)
Gisele Lobo Pappa, Michael T. M. Emmerich, Ana L. C. Bazzan, Will N. Browne, Kalyanmoy Deb, Carola Doerr, Marko Durasevic, Michael G. Epitropakis, Saemundur O. Haraldsson, Domagoj Jakobovic, Pascal Kerschke, Krzysztof Krawiec, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang
Tutorials at PPSN 2018. PPSN (2) (2018)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
When Hypermutations and Ageing Enable Artificial Immune Systems to Outperform Evolutionary Algorithms. CoRR (2018)
Robin C. Purshouse, Christine Zarges, Sylvain Cussat-Blanc, Michael G. Epitropakis, Marcus Gallagher, Thomas Jansen, Pascal Kerschke, Xiaodong Li, Fernando G. Lobo, Julian F. Miller, Pietro S. Oliveto, Mike Preuss, Giovanni Squillero, Alberto Paolo Tonda, Markus Wagner, Thomas Weise, Dennis Wilson, Borys Wróbel, Ales Zamuda
Workshops at PPSN 2018. PPSN (2) (2018)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem. PPSN (2) (2018)
Andrei Lissovoi, Pietro S. Oliveto
Computational Complexity Analysis of Genetic Programming. CoRR (2018)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
Fast Artificial Immune Systems. PPSN (2) (2018)
Samadhi Nallaperuma, Pietro S. Oliveto, Jorge Pérez Heredia, Dirk Sudholt
When is it beneficial to reject improvements? GECCO (2017)
Andrei Lissovoi, Pietro S. Oliveto, John Alasdair Warwicker
On the runtime analysis of generalised selection hyper-heuristics for pseudo-boolean optimisation. GECCO (2017)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2017. GECCO (Companion) (2017)
Dogan Corus, Pietro S. Oliveto, Donya Yazdani
On the runtime analysis of the opt-IA artificial immune system. GECCO (2017)
Per Kristian Lehre, Pietro S. Oliveto
Theoretical Analysis of Stochastic Search Algorithms. CoRR (2017)
Dogan Corus, Jun He, Thomas Jansen, Pietro S. Oliveto, Dirk Sudholt, Christine Zarges
On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation. Algorithmica 78 (2) (2017)
Dogan Corus, Pietro S. Oliveto
Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms. CoRR (2017)
Carola Doerr, Nicolas Bredèche, Enrique Alba, Thomas Bartz-Beielstein, Dimo Brockhoff, Benjamin Doerr, Gusz Eiben, Michael G. Epitropakis, Carlos M. Fonseca, Andreia P. Guerreiro, Evert Haasdijk, Jacqueline Heinerman, Julien Hubert, Per Kristian Lehre, Luigi Malagò, Juan Julián Merelo Guervós, Julian Francis Miller, Boris Naujoks, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Patricia Ryser-Welch, Giovanni Squillero, Jörg Stork, Dirk Sudholt, Alberto Paolo Tonda, L. Darrell Whitley, Martin Zaefferer
Tutorials at PPSN 2016. PPSN (2016)
Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton
Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms. PPSN (2016)
Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton
Escaping Local Optima with Diversity Mechanisms and Crossover. GECCO (2016)
Per Kristian Lehre, Pietro S. Oliveto
Runtime Analysis of Population-based Evolutionary Algorithms. GECCO (Companion) (2016)
Andrea Mambrini, Pietro S. Oliveto
On the Analysis of Simple Genetic Programming for Evolving Boolean Functions. EuroGP (2016)
Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton
Escaping Local Optima using Crossover with Emergent or Reinforced Diversity. CoRR (2016)
Pietro S. Oliveto, Tiago Paixão, Jorge Pérez Heredia, Dirk Sudholt, Barbora Trubenová
When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys. GECCO (2016)
Per Kristian Lehre, Pietro S. Oliveto
Runtime Analysis of Evolutionary Algorithms: Basic Introduction. GECCO (Companion) (2015)
Pietro S. Oliveto, Andrew M. Sutton
Editorial for the Special Issue on Theory of Evolutionary Algorithms 2014. Evol. Comput. 23 (4) (2015)
Pietro S. Oliveto, Carsten Witt
Improved time complexity analysis of the Simple Genetic Algorithm. Theor. Comput. Sci. 605 (2015)
Pietro S. Oliveto, Christine Zarges
Analysis of diversity mechanisms for optimisation in dynamic environments with low frequencies of change. Theor. Comput. Sci. 561 (2015)
Dogan Corus, Jun He, Thomas Jansen, Pietro S. Oliveto, Dirk Sudholt, Christine Zarges
On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations. GECCO (2015)
Pietro S. Oliveto, Dirk Sudholt, Christine Zarges
On the Runtime Analysis of Fitness Sharing Mechanisms. PPSN (2014)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of evolutionary algorithms: basic introduction. GECCO (Companion) (2014)
Pietro S. Oliveto, Dirk Sudholt
On the runtime analysis of stochastic ageing mechanisms. GECCO (2014)
Pietro S. Oliveto, Carsten Witt
On the runtime analysis of the Simple Genetic Algorithm. Theor. Comput. Sci. 545 (2014)
Pietro S. Oliveto, Carsten Witt
Improved runtime analysis of the simple genetic algorithm. GECCO (2013)
Pietro S. Oliveto, Christine Zarges
Analysis of diversity mechanisms for optimisation in dynamic environments with low frequencies of change. GECCO (2013)
Thomas Jansen, Pietro S. Oliveto, Christine Zarges
Approximating vertex cover using edge-based representations. FOGA (2013)
Per Kristian Lehre, Pietro S. Oliveto
Runtime analysis of evolutionary algorithms: basic introduction. GECCO (Companion) (2013)
Pietro S. Oliveto, Carsten Witt
On the analysis of the simple genetic algorithm. GECCO (2012)
Pietro S. Oliveto, Carsten Witt
Erratum: Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation. CoRR (2012)
Anastasia Athanasiou, Matteo De Felice, Giuseppe Oliveto, Pietro S. Oliveto
Evolutionary Algorithms for the Identification of Structural Systems in Earthquake Engineering. IJCCI (ECTA-FCTA) (2011)
Thomas Jansen, Pietro S. Oliveto, Christine Zarges
On the Analysis of the Immune-Inspired B-Cell Algorithm for the Vertex Cover Problem. ICARIS (2011)
Pietro S. Oliveto, Carsten Witt
Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation. Algorithmica 59 (3) (2011)
Frank Neumann, Pietro S. Oliveto, Günter Rudolph, Dirk Sudholt
On the effectiveness of crossover for migration in parallel evolutionary algorithms. GECCO (2011)
Timo Kötzing, Per Kristian Lehre, Frank Neumann, Pietro S. Oliveto
Ant colony optimization and the minimum cut problem. GECCO (2010)
Tobias Friedrich, Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
Analysis of Diversity-Preserving Mechanisms for Global Exploration. Evol. Comput. 17 (4) (2009)
Pietro S. Oliveto, Per Kristian Lehre, Frank Neumann
Theoretical analysis of rank-based mutation - combining exploration and exploitation. IEEE Congress on Evolutionary Computation (2009)
Pietro S. Oliveto, Jun He, Xin Yao
Analysis of the (1+1) -EA for Finding Approximate Solutions to Vertex Cover Problems. IEEE Trans. Evol. Comput. 13 (5) (2009)
Frank Neumann, Pietro S. Oliveto, Carsten Witt
Theoretical analysis of fitness-proportional selection: landscapes and efficiency. GECCO (2009)
Tobias Friedrich, Pietro S. Oliveto, Dirk Sudholt, Carsten Witt
Theoretical analysis of diversity mechanisms for global exploration. GECCO (2008)
Pietro S. Oliveto, Jun He, Xin Yao
Analysis of population-based evolutionary algorithms for the vertex cover problem. IEEE Congress on Evolutionary Computation (2008)
Pietro S. Oliveto, Carsten Witt
Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation. PPSN (2008)
Vincenzo Cutello, Giuseppe Nicosia, Mario Romeo, Pietro S. Oliveto
On the Convergence of Immune Algorithms. FOCI (2007)
Pietro S. Oliveto, Jun He, Xin Yao
Time complexity of evolutionary algorithms for combinatorial optimization: A decade of results. Int. J. Autom. Comput. 4 (3) (2007)
Pietro S. Oliveto, Jun He, Xin Yao
Evolutionary algorithms and the Vertex Cover problem. IEEE Congress on Evolutionary Computation (2007)

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Publication Activity (10 Years)

Top Topics

Top Venues

Pietro S. Oliveto