Per Kristian Lehre

Per Lehre
ORCID: 0000-0002-9521-1251

Colleges, School and Institutes

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Most downloaded publications

Level-based analysis of genetic algorithms and other search processes
Per Kristian Lehre, Oct 2018, In: IEEE Transactions on Evolutionary Computation. 22, 5, p. 707 - 719 13 p.

Research output: Contribution to journal › Article › peer-review

158 downloads
Runtime analysis of the (1+1) EA on computing unique input output sequences
Per Kristian Lehre & Xin Yao, 20 Feb 2014, In: Information Sciences. 259, p. 510-531

Research output: Contribution to journal › Article › peer-review

104 downloads
Surfing on the seascape: adaptation in a changing environment
Per Kristian Lehre & , Jul 2019, In: Evolution; international journal of organic evolution. 73, 7, p. 1356-1374 19 p.

Research output: Contribution to journal › Article › peer-review

84 downloads
Escaping local optima using crossover with emergent diversity
Per Kristian Lehre, , & , Jun 2018, In: IEEE Transactions on Evolutionary Computation. 22, 3, p. 484 - 497 14 p.

Research output: Contribution to journal › Article › peer-review

83 downloads
Level-based analysis of the population-based incremental learning algorithm
Per Kristian Lehre & Hai Nguyen, 5 Oct 2018, Proceedings of the 15th International Conference on Parallel Problem Solving from Nature 2018 (PPSN XV). 1 ed. Springer, Vol. 11101. 11 p. (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

77 downloads

Recent publications

Runtime analyses of population-based univariate estimation of distribution algorithms on LeadingOnes
Per Kristian Lehre & Hai Nguyen, 18 Jul 2021, (Accepted/In press) In: Algorithmica.

Research output: Contribution to journal › Article › peer-review

Non-elitist evolutionary algorithms excel in fitness landscapes with sparse deceptive regions and dense valleys
Per Kristian Lehre, 26 Jun 2021, GECCO '21: Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. Chicano, F. (ed.). Association for Computing Machinery (ACM), p. 1133–1141 9 p. (GECCO: Genetic and Evolutionary Computation Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

More precise runtime analyses of non-elitist EAs in uncertain environments
Per Kristian Lehre & , 2021, (Accepted/In press) GECCO '21: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. Association for Computing Machinery (ACM), (Genetic and Evolutionary Computation Conference (GECCO)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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