Search Results for author: Martin S. Krejca

Found 4 papers, 0 papers with code

The Univariate Marginal Distribution Algorithm Copes Well With Deception and Epistasis

no code implementations16 Jul 2020 Benjamin Doerr, Martin S. Krejca

In their recent work, Lehre and Nguyen (FOGA 2019) show that the univariate marginal distribution algorithm (UMDA) needs time exponential in the parent populations size to optimize the DeceptiveLeadingBlocks (DLB) problem.

Theory of Estimation-of-Distribution Algorithms

no code implementations14 Jun 2018 Martin S. Krejca, Carsten Witt

Estimation-of-distribution algorithms (EDAs) are general metaheuristics used in optimization that represent a more recent alternative to classical approaches like evolutionary algorithms.

First-Hitting Times Under Additive Drift

no code implementations22 May 2018 Timo Kötzing, Martin S. Krejca

As corollaries, the same is true for our upper bounds in the case of variable and multiplicative drift.

Escaping Local Optima using Crossover with Emergent or Reinforced Diversity

no code implementations10 Aug 2016 Duc-Cuong Dang, Tobias Friedrich, Timo Kötzing, Martin S. Krejca, Per Kristian Lehre, Pietro S. Oliveto, Dirk Sudholt, Andrew M. Sutton

This proves a sizeable advantage of all variants of the ($\mu$+1) GA compared to (1+1) EA, which requires time $\Theta(n^k)$.

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