Per Kristian Lehre

Publications

  1. 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

  2. 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

  3. Published

    Theoretical Runtime Analyses of Search Algorithms on the Test Data Generation for the Triangle Classification Problem

    Per Kristian Lehre & Xin Yao, 11 Apr 2008, p. 161-169. 9 p.

    Research output: Contribution to conference (unpublished)Paper

  4. Published

    Theoretical Runtime Analysis in Search Based Software Engineering, Research Report CSR-09-04

    Per Kristian Lehre & Xin Yao, 1 May 2009, Not Known.

    Research output: Book/ReportCommissioned report

  5. Published

    Unbiased black-box complexity of parallel search

    Per Kristian Lehre, 24 Sep 2014, Parallel Problem Solving from Nature – PPSN XIII: 13th International Conference Ljubljana, Slovenia, September 13-17, 2014 Proceedings. Bartz-Beielstein, T., Branke, J., Filipic, B. & Smith, J. (eds.). 1 ed. Springer, p. 892-901 10 p. (Lecture Notes in Computer Science ; vol. 8672).

    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
  8. Published
  9. 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

  10. Published

    When is an estimation of distribution algorithm better than an evolutionary algorithm?

    Per Kristian Lehre & Xin Yao, 18 May 2009, p. 1470-1477. 8 p.

    Research output: Contribution to conference (unpublished)Paper

  11. 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

  12. 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

  13. 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

  14. Published

    Theory driven design of efficient genetic algorithms for a classical graph problem

    Per Kristian Lehre, 1 Jan 2018, In: Operations Research/ Computer Science Interfaces Series. 62, p. 125-140 16 p.

    Research output: Contribution to journalArticlepeer-review

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

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