Dogan Corus

According to our database, Dogan Corus authored at least 21 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

On the Generalisation Performance of Geometric Semantic Genetic Programming for Boolean Functions: Learning Block Mutations.

Dogan Corus, Pietro S. Oliveto

ACM Trans. Evol. Learn. Optim., December, 2024

2021

On Steady-State Evolutionary Algorithms and Selective Pressure: Why Inverse Rank-Based Allocation of Reproductive Trials Is Best.

Dogan Corus, Andrei Lissovoi, Pietro S. Oliveto, Carsten Witt

ACM Trans. Evol. Learn. Optim., 2021

Fast Immune System-Inspired Hypermutation Operators for Combinatorial Optimization.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

IEEE Trans. Evol. Comput., 2021

Automatic adaptation of hypermutation rates for multimodal optimisation.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Proceedings of the FOGA '21: Foundations of Genetic Algorithms XVI, 2021

2020

When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Theor. Comput. Sci., 2020

Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

CoRR, 2020

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

Dogan Corus, Pietro S. Oliveto

Algorithmica, 2020

2019

Artificial immune systems can find arbitrarily good approximations for the NP-hard number partitioning problem.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Artif. Intell., 2019

On inversely proportional hypermutations with mutation potential.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

2018

Runtime analysis of evolutionary algorithms with complex fitness evaluation mechanisms.

Dogan Corus

PhD thesis, 2018

Standard Steady State Genetic Algorithms Can Hillclimb Faster Than Mutation-Only Evolutionary Algorithms.

Dogan Corus, Pietro S. Oliveto

IEEE Trans. Evol. Comput., 2018

Level-Based Analysis of Genetic Algorithms and Other Search Processes.

Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre

IEEE Trans. Evol. Comput., 2018

Fast Artificial Immune Systems.

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

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

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Proceedings of the Parallel Problem Solving from Nature - PPSN XV, 2018

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

Dogan Corus, Pietro S. Oliveto

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018

2017

On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation.

Dogan Corus, Jun He, Thomas Jansen, Pietro S. Oliveto, Dirk Sudholt, Christine Zarges

Algorithmica, 2017

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

Dogan Corus, Pietro S. Oliveto, Donya Yazdani

Proceedings of the Genetic and Evolutionary Computation Conference, 2017

2016

A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms.

Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan

Evol. Comput., 2016

2015

On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations.

Dogan Corus, Jun He, Thomas Jansen, Pietro S. Oliveto, Dirk Sudholt, Christine Zarges

Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2014

A Parameterized Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms.

Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan

CoRR, 2014

2013

The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation.

Dogan Corus, Per Kristian Lehre, Frank Neumann

Proceedings of the Genetic and Evolutionary Computation Conference, 2013