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ORCIDDogan Corus
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2020 – today
- 2021
[j9]Dogan Corus
, Pietro S. Oliveto, Donya Yazdani:
Fast Immune System-Inspired Hypermutation Operators for Combinatorial Optimization. IEEE Trans. Evol. Comput. 25(5): 956-970 (2021)- [j8]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): 2:1-2:38 (2021) - [c10]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
Automatic adaptation of hypermutation rates for multimodal optimisation. FOGA 2021: 4:1-4:12 - [i10]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 abs/2103.10394 (2021) - 2020
- [j7]Dogan Corus, Pietro S. Oliveto:
On the Benefits of Populations for the Exploitation Speed of Standard Steady-State Genetic Algorithms. Algorithmica 82(12): 3676-3706 (2020) - [j6]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms. Theor. Comput. Sci. 832: 166-185 (2020) - [i9]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
Fast Immune System Inspired Hypermutation Operators for Combinatorial Optimisation. CoRR abs/2009.00990 (2020)
2010 – 2019
- 2019
- [j5]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: 180-196 (2019) - [c9]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
On inversely proportional hypermutations with mutation potential. GECCO 2019: 215-223 - [c8]Dogan Corus, Pietro S. Oliveto:
On the benefits of populations for the exploitation speed of standard steady-state genetic algorithms. GECCO 2019: 1452-1460 - [i8]Dogan Corus, Pietro S. Oliveto:
On the Benefits of Populations on the Exploitation Speed of Standard Steady-State Genetic Algorithms. CoRR abs/1903.10976 (2019) - [i7]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
On Inversely Proportional Hypermutations with Mutation Potential. CoRR abs/1903.11674 (2019) - 2018
- [b1]Dogan Corus:
Runtime analysis of evolutionary algorithms with complex fitness evaluation mechanisms. University of Nottingham, UK, 2018 - [j4]Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-Based Analysis of Genetic Algorithms and Other Search Processes. IEEE Trans. Evol. Comput. 22(5): 707-719 (2018) - [j3]Dogan Corus, Pietro S. Oliveto:
Standard Steady State Genetic Algorithms Can Hillclimb Faster Than Mutation-Only Evolutionary Algorithms. IEEE Trans. Evol. Comput. 22(5): 720-732 (2018) - [c7]Dogan Corus, Pietro S. Oliveto:
Standard steady state genetic algorithms can hillclimb faster than evolutionary algorithms using standard bit mutation. GECCO (Companion) 2018: 11-12 - [c6]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem. PPSN (2) 2018: 16-28 - [c5]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
Fast Artificial Immune Systems. PPSN (2) 2018: 67-78 - [i6]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
When Hypermutations and Ageing Enable Artificial Immune Systems to Outperform Evolutionary Algorithms. CoRR abs/1804.01314 (2018) - [i5]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
Fast Artificial Immune Systems. CoRR abs/1806.00299 (2018) - [i4]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
Artificial Immune Systems Can Find Arbitrarily Good Approximations for the NP-Hard Partition Problem. CoRR abs/1806.00300 (2018) - 2017
- [j2]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): 714-740 (2017) - [c4]Dogan Corus, Pietro S. Oliveto, Donya Yazdani:
On the runtime analysis of the opt-IA artificial immune system. GECCO 2017: 83-90 - [i3]Dogan Corus, Pietro S. Oliveto:
Standard Steady State Genetic Algorithms Can Hillclimb Faster than Mutation-only Evolutionary Algorithms. CoRR abs/1708.01571 (2017) - 2016
- [j1]Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan:
A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. Evol. Comput. 24(1): 183-203 (2016) - 2015
- [c3]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: 1399-1406 - 2014
- [c2]Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-Based Analysis of Genetic Algorithms and Other Search Processes. PPSN 2014: 912-921 - [i2]Dogan Corus, Per Kristian Lehre, Frank Neumann, Mojgan Pourhassan:
A Parameterized Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. CoRR abs/1401.1905 (2014) - [i1]Dogan Corus, Duc-Cuong Dang, Anton V. Eremeev, Per Kristian Lehre:
Level-based Analysis of Genetic Algorithms and other Search Processes. CoRR abs/1407.7663 (2014) - 2013
- [c1]Dogan Corus, Per Kristian Lehre, Frank Neumann:
The generalized minimum spanning tree problem: a parameterized complexity analysis of bi-level optimisation. GECCO 2013: 519-526
Coauthor Index
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