Items where authors include "Corus, D."

Article

Corus, D., Oliveto, P.S. and Yazdani, D. (2021) Fast immune system-inspired hypermutation operators for combinatorial optimization. IEEE Transactions on Evolutionary Computation, 25 (5). pp. 956-970. ISSN 1089-778X

Corus, D., Lissovoi, A., Oliveto, P. et al. (1 more author) (2021) On steady-state evolutionary algorithms and selective pressure: Why inverse rank-based allocation of reproductive trials is best. ACM Transactions on Evolutionary Learning and Optimization, 1 (1). 2. ISSN 2688-299X

Corus, D. and Oliveto, P.S. (2020) On the benefits of populations for the exploitation speed of standard steady-state genetic algorithms. Algorithmica, 82 (12). pp. 3676-3706. ISSN 0178-4617

Corus, D., Oliveto, P.S. and Yazdani, D. (2020) When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms. Theoretical Computer Science, 832. pp. 166-185. ISSN 0304-3975

Corus, D., Oliveto, P.S. and Yazdani, D. (2019) Artificial immune systems can find arbitrarily good approximations for the NP-hard number partitioning problem. Artificial Intelligence, 274. pp. 180-196. ISSN 0004-3702

Corus, D. and Oliveto, P.S. (2018) Standard steady state genetic algorithms can hillclimb faster than mutation-only evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 22 (5). pp. 720-732. ISSN 1089-778X

Corus, D., He, J., Jansen, T. et al. (3 more authors) (2017) On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation. Algorithmica, 78 (2). pp. 714-740. ISSN 0178-4617

Corus, D., Lehre, P.K., Neumann, F. et al. (1 more author) (2016) A Parameterised Complexity Analysis of Bi-level Optimisation with Evolutionary Algorithms. Evolutionary Computation, 24 (1). pp. 183-203. ISSN 1063-6560

Proceedings Paper

Corus, D., Oliveto, P.S. and Yazdani, D. (2019) On inversely proportional hypermutations with mutation potential. In: GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2019, 13-17 Jul 2019, Prague, Czech Republic. ACM , pp. 215-223. ISBN 978-1-4503-6111-8

Corus, D. and Oliveto, P.S. (2019) On the benefits of populations on the exploitation speed of standard steady-state genetic algorithms. In: GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference. GECCO '19, 13-17 Jul 2019, Prague, Czech Republic. ACM , pp. 1452-1460. ISBN 978-1-4503-6111-8

Corus, D., Oliveto, P.S. and Yazdani, D. (2018) Artificial Immune Systems can find arbitrarily good approximations for the NP-Hard partition problem. In: Auger, A., Fonseca, C., Lourenço, N., Machado , P., Paquete, L. and Whitley, D., (eds.) Parallel Problem Solving from Nature – PPSN XV, PT II. PPSN: 15th International Conference on Parallel Problem Solving from Nature, 08-12 Sep 2018, Coimbra, Portugal. Lecture Notes in Computer Science, 11102 . Springer, Cham , pp. 16-28. ISBN 9783319992587

Corus, D., Dang, D.C., Eremeev, A.V. et al. (1 more author) (2014) Level-Based Analysis of Genetic Algorithms and Other Search Processes. In: Parallel Problem Solving from Nature – PPSN XIII. The 13th PPSN: International Conference on Parallel Problem Solving from Nature, September 13-17, 2014, Ljubljana, Slovenia. Lecture Notes in Computer Science (8672). Springer , pp. 912-921.