An Extended Jump Functions Benchmark for the Analysis of Randomized Search Heuristics
Author:
Funder
Agence Nationale de la Recherche
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Computer Science Applications,General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s00453-022-00977-1.pdf
Reference68 articles.
1. Antipov, D., Buzdalov, M., Doerr, B.: Fast mutation in crossover-based algorithms. In: Genetic and Evolutionary Computation Conference, GECCO 2020, pp. 1268–1276. ACM (2020)
2. Antipov, D., Buzdalov, M., Doerr, B.: First steps towards a runtime analysis when starting with a good solution. In: Parallel Problem Solving From Nature, PPSN 2020, Part II, pp. 560–573. Springer (2020)
3. Antipov, D., Buzdalov, M., Doerr, B.: Lazy parameter tuning and control: choosing all parameters randomly from a power-law distribution. In: Genetic and Evolutionary Computation Conference, GECCO 2021, pp. 1115–1123. ACM (2021)
4. Auger, A., Doerr, B., (eds).: Theory of Randomized Search Heuristics. World Scientific Publishing (2011)
5. Antipov, D., Doerr, B.: Runtime analysis of a heavy-tailed $$(1+(\lambda , \lambda ))$$ genetic algorithm on jump functions. In: Parallel Problem Solving From Nature, PPSN 2020, Part II, pp. 545–559. Springer (2020)
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