Pietro Simone Oliveto

发表

Approximating vertex cover using edge-based representations

Thomas Jansen, Pietro Simone Oliveto, Christine Zarges, 2013, FOGA XII '13.

On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions

Pietro Simone Oliveto, Andrei Lissovoi, Andrei Lissovoi, 2018, AAAI.

Theoretical analysis of rank-based mutation - combining exploration and exploitation

Per Kristian Lehre, Pietro Simone Oliveto, Frank Neumann, 2009, 2009 IEEE Congress on Evolutionary Computation.

Workshops at PPSN 2018

Pietro Simone Oliveto, Christine Zarges, Ales Zamuda, 2018, PPSN.

Erratum: Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

Pietro Simone Oliveto, Carsten Witt, 2008, PPSN.

Evolutionary algorithms and the Vertex Cover problem

Pietro Simone Oliveto, Xin Yao, Jun He, 2007, 2007 IEEE Congress on Evolutionary Computation.

Escaping Local Optima using Crossover with Emergent or Reinforced Diversity pdf

Duc-Cuong Dang, Per Kristian Lehre, Pietro Simone Oliveto, 2016, ArXiv.

Hyper-heuristics Can Achieve Optimal Performance for Pseudo-Boolean Optimisation pdf

Pietro Simone Oliveto, Andrei Lissovoi, John Alasdair Warwicker, 2018, ArXiv.

Analysis of the performance of algorithm configurators for search heuristics with global mutation operators

Pietro Simone Oliveto, Dirk Sudholt, George T. Hall, 2020, GECCO.

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Theoretical Analysis of Diversity Mechanisms for Global Exploration Theoretical Analysis of Diversity Mechanisms for Global Exploration

Pietro Simone Oliveto, Dirk Sudholt, Tobias Friedrich, 2022 .

Evolving boolean functions with conjunctions and disjunctions via genetic programming

Pietro Simone Oliveto, Benjamin Doerr, Andrei Lissovoi, 2019, GECCO.

Co-evolution of Optimal Agents for the Alternating Offers Bargaining Game

Pietro Simone Oliveto, Xin Yao, Arjun Chandra, 2010, EvoApplications.

Standard steady state genetic algorithms can hillclimb faster than evolutionary algorithms using standard bit mutation

Pietro Simone Oliveto, Dogan Corus, P. S. Oliveto, 2018, GECCO.

Theoretical analysis of fitness-proportional selection: landscapes and efficiency

Pietro Simone Oliveto, Frank Neumann, Carsten Witt, 2009, GECCO.

On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations

Thomas Jansen, Pietro Simone Oliveto, Dirk Sudholt, 2015, GECCO.

On the Convergence of Immune Algorithms

Pietro Simone Oliveto, Vincenzo Cutello, Giuseppe Nicosia, 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

Runtime analysis of evolutionary algorithms: basic introduction: introductory tutorial at GECCO 2019

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2019, GECCO.

On the effectiveness of crossover for migration in parallel evolutionary algorithms

Pietro Simone Oliveto, Dirk Sudholt, Günter Rudolph, 2011, GECCO '11.

On the analysis of the simple genetic algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2012, GECCO '12.

When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys

Pietro Simone Oliveto, Dirk Sudholt, Tiago Paixão, 2016, GECCO.

Editorial for the Special Issue on Theory of Evolutionary Algorithms 2014

Pietro Simone Oliveto, Andrew M. Sutton, 2015, Evolutionary Computation.

Improved time complexity analysis of the Simple Genetic Algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2015, Theor. Comput. Sci..

Analysis of an evolutionary algorithm with HyperMacromutation and stop at first constructive mutation heuristic for solving trap functions

Pietro Simone Oliveto, Vincenzo Cutello, Giuseppe Nicosia, 2006, SAC.

Tutorials at PPSN 2016

Per Kristian Lehre, Pietro Simone Oliveto, Dirk Sudholt, 2016, PPSN.

On the runtime analysis of generalised selection hyper-heuristics for pseudo-boolean optimisation

Pietro Simone Oliveto, Andrei Lissovoi, John Alasdair Warwicker, 2017, GECCO.

Theoretical Analysis of Stochastic Search Algorithms

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2017, Handbook of Heuristics.

On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation

Thomas Jansen, Pietro Simone Oliveto, Dirk Sudholt, 2016, Algorithmica.

Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem

Pietro Simone Oliveto, Dogan Corus, Donya Yazdani, 2018, PPSN.

Analysis of Diversity-Preserving Mechanisms for Global Exploration

Pietro Simone Oliveto, Dirk Sudholt, Tobias Friedrich, 2009, Evolutionary Computation.

Evolutionary Algorithms for the Identification of Structural Systems in Earthquake Engineering

Pietro Simone Oliveto, Matteo De Felice, Giuseppe Oliveto, 2011, IJCCI.

Tutorials at PPSN 2018

Roman Senkerik, Per Kristian Lehre, Pietro Simone Oliveto, 2018, PPSN.

Runtime Analysis of Population-based Evolutionary Algorithms

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2016, GECCO.

On the Benefits of Populations for the Exploitation Speed of Standard Steady-State Genetic Algorithms

Pietro Simone Oliveto, Dogan Corus, P. S. Oliveto, 2019, Algorithmica.

On the Analysis of Simple Genetic Programming for Evolving Boolean Functions

Pietro Simone Oliveto, Andrea Mambrini, P. S. Oliveto, 2016, EuroGP.

Emergence of Diversity and Its Benefits for Crossover in Genetic Algorithms

Duc-Cuong Dang, Per Kristian Lehre, Pietro Simone Oliveto, 2016, PPSN.

How to Escape Local Optima in Black Box Optimisation: When Non-elitism Outperforms Elitism

Pietro Simone Oliveto, Dirk Sudholt, Tiago Paixão, 2017, Algorithmica.

When is it beneficial to reject improvements?

Pietro Simone Oliveto, Dirk Sudholt, Samadhi Nallaperuma, 2017, GECCO.

On the Analysis of Trajectory-Based Search Algorithms: When is it Beneficial to Reject Improvements?

Pietro Simone Oliveto, Dirk Sudholt, Samadhi Nallaperuma, 2018, Algorithmica.

Analysis of diversity mechanisms for optimisation in dynamic environments with low frequencies of change

Pietro Simone Oliveto, Christine Zarges, 2015, Theor. Comput. Sci..

Analysis of the $(1+1)$-EA for Finding Approximate Solutions to Vertex Cover Problems

Pietro Simone Oliveto, Xin Yao, Jun He, 2009, IEEE Transactions on Evolutionary Computation.

Runtime analysis of population-based evolutionary algorithms: introductory tutorial at GECCO 2017

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2017, GECCO.

On the Runtime Analysis of Fitness Sharing Mechanisms

Pietro Simone Oliveto, Dirk Sudholt, Christine Zarges, 2014, PPSN.

When Hypermutations and Ageing Enable Artificial Immune Systems to Outperform Evolutionary Algorithms

Pietro Simone Oliveto, Dogan Corus, Donya Yazdani, 2018, Theor. Comput. Sci..

On the runtime analysis of the Simple Genetic Algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2014, Theor. Comput. Sci..

Runtime analysis of evolutionary algorithms: basic introduction

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2018, GECCO.

Escaping Local Optima with Diversity Mechanisms and Crossover

Duc-Cuong Dang, Per Kristian Lehre, Pietro Simone Oliveto, 2016, GECCO.

On inversely proportional hypermutations with mutation potential

Pietro Simone Oliveto, Dogan Corus, Donya Yazdani, 2019, GECCO.

Analysis of population-based evolutionary algorithms for the vertex cover problem

Pietro Simone Oliveto, Xin Yao, Jun He, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Improved runtime analysis of the simple genetic algorithm

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2013, GECCO '13.

Simplified Drift Analysis for Proving Lower Bounds in Evolutionary Computation

Pietro Simone Oliveto, Carsten Witt, C. Witt, 2008, Algorithmica.

Computational Complexity Analysis of Genetic Programming pdf

Pietro Simone Oliveto, Andrei Lissovoi, Andrei Lissovoi, 2018, Theory of Evolutionary Computation.

Runtime Analysis of Evolutionary Algorithms: Basic Introduction

Per Kristian Lehre, Pietro Simone Oliveto, 2015, GECCO.

Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation

Per Kristian Lehre, Pietro Simone Oliveto, Frank Neumann, 2010, PPSN.

How Theoretical Analyses Can Impact Practical Applications of Evolutionary Computation

Pietro Simone Oliveto, 2019, IJCCI.

On the runtime analysis of the opt-IA artificial immune system

Pietro Simone Oliveto, Dogan Corus, Donya Yazdani, 2017, GECCO.

On the runtime analysis of stochastic ageing mechanisms

Pietro Simone Oliveto, Dirk Sudholt, Dirk Sudholt, 2014, GECCO.

On the impact of the cutoff time on the performance of algorithm configurators

Pietro Simone Oliveto, Dirk Sudholt, George T. Hall, 2019, GECCO.

Ant colony optimization and the minimum cut problem

Per Kristian Lehre, Pietro Simone Oliveto, Frank Neumann, 2010, GECCO '10.

Runtime analysis of evolutionary algorithms: basic introduction

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2014, GECCO.

On the Analysis of the Immune-Inspired B-Cell Algorithm for the Vertex Cover Problem

Thomas Jansen, Pietro Simone Oliveto, Christine Zarges, 2011, ICARIS.

Analysis of diversity mechanisms for optimisation in dynamic environments with low frequencies of change

Pietro Simone Oliveto, Christine Zarges, P. S. Oliveto, 2013, GECCO '13.

Fast Artificial Immune Systems pdf

Pietro Simone Oliveto, Dogan Corus, Donya Yazdani, 2018, PPSN.

Runtime analysis of evolutionary algorithms: basic introduction

Per Kristian Lehre, Pietro Simone Oliveto, P. Lehre, 2013, GECCO.

On the runtime analysis of selection hyper-heuristics with adaptive learning periods

Pietro Simone Oliveto, Benjamin Doerr, Andrei Lissovoi, 2018, GECCO.