2021
DOI: 10.1162/evco_a_00283
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Lower Bounds for Non-Elitist Evolutionary Algorithms via Negative Multiplicative Drift

Abstract: A decent number of lower bounds for non-elitist population-based evolutionary algorithms has been shown by now. Most of them are technically demanding due to the (hard to avoid) use of negative drift theorems — general results which translate an expected movement away from the target into a high hitting time. We propose a simple negative drift theorem for multiplicative drift scenarios and show that it can simplify existing analyses. We discuss in more detail Lehre's (PPSN 2010) negative drift in populations … Show more

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Cited by 12 publications
(4 citation statements)
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“…, which is the left hand side of (7). Finally, we note for later reference that by an analogous computation, ( 8) and ( 9) also hold with U and Ũ reversed, so for all vectors v,…”
Section: Satisfies the Following Conditionsmentioning
confidence: 76%
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“…, which is the left hand side of (7). Finally, we note for later reference that by an analogous computation, ( 8) and ( 9) also hold with U and Ũ reversed, so for all vectors v,…”
Section: Satisfies the Following Conditionsmentioning
confidence: 76%
“…To highlight just one result, the (μ + 1)-EA with standard mutation rate 1/n fails on some monotone functions if the population size μ is too large (but still constant in n) [26]. Other algorithm-specific failure modes include (i) non-elitist selection strategies with too small offspring reproductive rate (e.g., comma strategies with small offspring population size) [1,5,7,11,17,30]; (ii) elitist algorithms (and also some non-elitist strategies) in certain landscapes with deceptive local optima [3,4];…”
Section: The Application: Twolinmentioning
confidence: 99%
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“…This condition was described in [57] as negative multiplicative drift with an additive disturbance (in [57] only lower hitting time bounds were given, while we will prove upper bounds). An equilibrium state with zero drift is attained for…”
Section: Equilibria and Time Boundsmentioning
confidence: 99%