The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation. - Dogan Corus; Per Kristian Lehre; Frank Neumann 001 (GECCO, 2013)

A Parameterized Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. - Dogan Corus; Per Kristian Lehre; Frank Neumann 001; Mojgan Pourhassan (CoRR, 2014)

On Easiest Functions for Somatic Contiguous Hypermutations And Standard Bit Mutations. - Dogan Corus; Jun He 004; Thomas Jansen 001; Pietro S. Oliveto; Dirk Sudholt; Christine Zarges (GECCO, 2015)

A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. - Dogan Corus; Per Kristian Lehre; Frank Neumann 001; Mojgan Pourhassan (Evol. Comput., 2016)

On the runtime analysis of the opt-IA artificial immune system. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (GECCO, 2017)

On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation. - Dogan Corus; Jun He 004; Thomas Jansen 001; Pietro S. Oliveto; Dirk Sudholt; Christine Zarges (Algorithmica, 2017)

Standard steady state genetic algorithms can hillclimb faster than evolutionary algorithms using standard bit mutation. - Dogan Corus; Pietro S. Oliveto (GECCO (Companion), 2018)

Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (PPSN (2), 2018)

Fast Artificial Immune Systems. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (PPSN (2), 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)

Standard Steady State Genetic Algorithms Can Hillclimb Faster Than Mutation-Only Evolutionary Algorithms. - Dogan Corus; Pietro S. Oliveto (IEEE Trans. Evol. Comput., 2018)

Runtime analysis of evolutionary algorithms with complex fitness evaluation mechanisms. - Dogan Corus (2018)

On inversely proportional hypermutations with mutation potential. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (GECCO, 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 the Benefits of Populations for the Exploitation Speed of Standard Steady-State Genetic Algorithms. - Dogan Corus; Pietro S. Oliveto (Algorithmica, 2020)

Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (CoRR, 2020)

When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (Theor. Comput. Sci., 2020)

Automatic adaptation of hypermutation rates for multimodal optimisation. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (FOGA, 2021)

Fast Immune System-Inspired Hypermutation Operators for Combinatorial Optimization. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (IEEE Trans. Evol. Comput., 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)

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., 2024)

Fast Contiguous Somatic Hypermutations for Single-Objective Optimisation and Multi-Objective Optimisation Via Decomposition. - Dogan Corus; Pietro S. Oliveto; Donya Yazdani (AAAI, 2025)

Hybrid Selection Allows Steady-State Evolutionary Algorithms to Control the Selective Pressure in Multimodal Optimisation. - Dogan Corus; Pietro S. Oliveto; Feiyang Zheng (GECCO, 2025)