Per Kristian Lehre

Publications

  1. Published

    A parameterised complexity analysis of bi-level optimisation with evolutionary algorithms

    Per Kristian Lehre, & , 1 Mar 2016, In: Evolutionary Computation. 24, 1, p. 183-203 21 p.

    Research output: Contribution to journalArticlepeer-review

  2. Published

    Accessibility and Runtime Between Convex Neutral Networks

    Per Kristian Lehre, , , , & , 1 Jan 2006, p. 734-741. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  3. Published

    Accessibility between Neutral Networks in Indirect Genotype-Phenotype Mappings

    Per Kristian Lehre, & , 1 Jan 2005, p. 419-426. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  4. Published
  5. Published

    Ant Colony Optimization and the Minimum Cut Problem

    Per Kristian Lehre, & Pietro Oliveto, 11 Jul 2010, Proceedings of the 12th annual conference on Genetic and evolutionary computation. p. 1393-1400 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  6. Published

    Black-box complexity of parallel search with distributed populations

    Per Kristian Lehre & , 17 Jan 2015, FOGA 2015 - Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII. Association for Computing Machinery , p. 3-15 13 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  7. Published

    Black-box search by unbiased variation

    Per Kristian Lehre & , 2010, Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10. p. 1441-1448 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  8. Published

    Concentrated hitting times of randomized search heuristics with variable drift

    Per Kristian Lehre & , 2014, Algorithms and Computation - 25th International Symposium, ISAAC 2014, Proceedings. Ahn, H-K. & Shin, C-S. (eds.). Springer Verlag, p. 686-697 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8889).

    Research output: Chapter in Book/Report/Conference proceedingChapter

  9. Published

    Crossover Can Be Constructive When Computing Unique Input Output Sequences

    Per Kristian Lehre, Xin Yao, , , , , , , , , , , & , 1 Dec 2008, p. 595-604. 10 p.

    Research output: Contribution to conference (unpublished)Paper

  10. Published
  11. Published

    Crossover can be constructive when computing unique input–output sequences

    Per Kristian Lehre & Xin Yao, 1 Sep 2011, In: Soft Computing. 15, 9, p. 1675-1687 13 p.

    Research output: Contribution to journalArticle

  12. Published

    Developmental Mappings and Phenotypic Complexity

    Per Kristian Lehre & , 1 Jan 2003, p. 62-68. 7 p.

    Research output: Contribution to conference (unpublished)Paper

  13. Published

    Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change

    Philipp Rohlfshagen, Per Kristian Lehre & Xin Yao, 12 Jul 2009, Proceedings of the 11th Annual conference on Genetic and evolutionary computation. p. 1713-1720 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  14. Published

    Efficient optimisation of noisy fitness functions with population-based evolutionary algorithms

    Per Kristian Lehre, 17 Jan 2015, FOGA 2015 - Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII. Association for Computing Machinery , p. 62-68 7 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  15. Published

    Emergence of diversity and its benefits for crossover in genetic algorithms

    Per Kristian Lehre, , & , 31 Aug 2016, Parallel Problem Solving from Nature - 14th International Conference, PPSN 2016, Proceedings. Springer Verlag, Vol. 9921 LNCS. p. 890-900 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9921 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  16. Accepted/In press

    Escaping Local Optima with Non-Elitist Evolutionary Algorithms

    Per Kristian Lehre, 2 Dec 2020, (Accepted/In press) Proceedings of AAAI 2021. AAAI Press

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

  17. Published

    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 journalArticlepeer-review

  18. Published

    Escaping local optima with diversity mechanisms and crossover

    Per Kristian Lehre, , & , 20 Jul 2016, GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference. Association for Computing Machinery , p. 645-652 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  19. Published

    Evolution under partial information

    Per Kristian Lehre, 2014, GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. Association for Computing Machinery , p. 1359-1366 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  20. Published

    Evolved Digital Circuits and Genome Complexity

    Per Kristian Lehre, , , , , , & , 1 Jan 2005, p. 79-86. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  21. Published

    Fixed Parameter Evolutionary Algorithms and Maximum Leaf Spanning Trees: A Matter of Mutation

    Per Kristian Lehre, , Pietro Oliveto, , , & , 1 Sep 2010, p. 204-213. 10 p.

    Research output: Contribution to conference (unpublished)Paper

  22. Published

    Improved runtime bounds for the univariate marginal distribution algorithm via anti-concentration

    Per Kristian Lehre & Hai Nguyen, 1 Jul 2017, GECCO '17 Proceedings of the Genetic and Evolutionary Computation Conference. Association for Computing Machinery , p. 1383-1390 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  23. Published

    Level-based analysis of genetic algorithms and other search processes

    Per Kristian Lehre, 2014, Parallel Problem Solving from Nature – PPSN XIII: 13th International Conference, Ljubljana, Slovenia, September 13-17, 2014. Proceedings. Springer, p. 912-921 10 p. (Lecture Notes in Computer Science; vol. 8672).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  24. Published

    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 journalArticlepeer-review

  25. Published

    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 proceedingConference contribution

  26. Published

    Level-based analysis of the univariate marginal distribution algorithm

    Per Kristian Lehre & Hai Nguyen, 15 Feb 2019, In: Algorithmica. 81, 2, p. 668-702 35 p.

    Research output: Contribution to journalArticlepeer-review

  27. Published

    Limits to learning in reinforcement learning hyper-heuristics

    Per Kristian Lehre, 2016, Evolutionary Computation in Combinatorial Optimization - 16th European Conference, EvoCOP 2016, Proceedings. Springer Verlag, Vol. 9595. p. 170-185 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9595).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  28. Accepted/In press

    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 proceedingConference contribution

  29. Published

    Non-Uniform Mutation Rates for Problems with Unknown Solution Lengths

    Per Kristian Lehre & Xin Yao, 9 Jan 2011, p. 173-180. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  30. Published

    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 proceedingConference contribution

  31. Published

    On the Effect of Populations in Evolutionary Multi-Objective Optimisation

    Per Kristian Lehre, 1 Oct 2010, In: Evolutionary Computation. 18, 3, p. 335-356 22 p.

    Research output: Contribution to journalArticle

  32. Published
  33. Published

    On the effect of populations in evolutionary multi-objective optimization

    Per Kristian Lehre, 1 Jan 2006, p. 651-658. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  34. Published

    On the impact of the mutation-selection balance on the runtime of evolutionary algorithms

    Per Kristian Lehre & Xin Yao, 11 Jan 2009, p. 47-58. 12 p.

    Research output: Contribution to conference (unpublished)Paper

  35. Published

    On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help

    Per Kristian Lehre & Hai Nguyen, 27 Aug 2019, Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms (FOGA '19). New York, NY, USA: Association for Computing Machinery (ACM), p. 154-168 15 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  36. Published

    Parallel black-box complexity with tail bounds

    Per Kristian Lehre & , 4 Dec 2019, In: IEEE Transactions on Evolutionary Computation. p. 1-15 15 p.

    Research output: Contribution to journalArticlepeer-review

  37. Published

    Populations Can Be Essential in Tracking Dynamic Optima

    Per Kristian Lehre, 1 Jun 2017, In: Algorithmica. 78, 2, p. 660-680 21 p.

    Research output: Contribution to journalArticlepeer-review

  38. Published

    Populations can be essential in dynamic optimisation

    Per Kristian Lehre, 11 Jul 2015, GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference. Association for Computing Machinery , p. 1407-1414 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  39. Published

    Refined upper bounds on the expected runtime of non-elitist populations from fitness-levels

    Per Kristian Lehre, 2014, GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference. Association for Computing Machinery , p. 1367-1374 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  40. Published

    Runtime Analysis of Non-elitist Populations: From Classical Optimisation to Partial Information

    Per Kristian Lehre, 1 Jul 2016, In: Algorithmica. 75, 3, p. 428-461 34 p.

    Research output: Contribution to journalArticlepeer-review

  41. Accepted/In press

    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 journalArticlepeer-review

  42. Published

    Runtime analysis of (1+1) EA on computing unique input output sequences

    Per Kristian Lehre & Xin Yao, 1 Jan 2007, p. 1882-1889. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  43. Published

    Runtime analysis of (1+l) EA on computing unique input output sequences

    Per Kristian Lehre & Xin Yao, 1 Jan 2007, IEEE Congress on Evolutionary Computation, 2007. CEC 2007.. Institute of Electrical and Electronics Engineers (IEEE), p. 1882-1889 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  44. Published

    Runtime analysis of search heuristics on software engineering problems

    Per Kristian Lehre & Xin Yao, 1 Mar 2009, In: Frontiers of Computer Science in China. 3, 1, p. 64-72 9 p.

    Research output: Contribution to journalArticle

  45. Published

    Runtime analysis of selection hyper-heuristics with classical learning mechanisms

    Per Kristian Lehre, 16 Sep 2014, Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers (IEEE), p. 2515-2523 9 p. 6900602. (IEEE Congress on Evolutionary Computation (CEC); vol. 2014).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  46. Published

    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 journalArticlepeer-review

  47. Published

    Runtime analysis of the univariate marginal distribution algorithm under low selective pressure and prior noise

    Per Kristian Lehre & Hai Nguyen, 13 Jul 2019, The Genetic and Evolutionary Computation Conference 2019 (GECCO 2019). López-Ibáñez, M. (ed.). Association for Computing Machinery (ACM), p. 1497-1505 9 p. (GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  48. Published
  49. Published

    Self-adaptation of mutation rates in non-elitist populations

    Per Kristian Lehre, 31 Aug 2016, PPSN 2016: Parallel Problem Solving from Nature – PPSN XIV . Handl, J., Hart, E., Lewis, P. R., López-Ibáñez, M., Ochoa, G. & Paechter, B. (eds.). Springer Verlag, p. 803-813 11 p. (Lecture Notes in Computer Science (LNCS); vol. 9921 )(Theoretical Computer Science and General Issues (LNTCS); vol. 9921).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  50. Published

    Simplified runtime analysis of estimation of distribution algorithms

    Per Kristian Lehre, 11 Jul 2015, GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference. Association for Computing Machinery , p. 513-518 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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