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20242026
most citedNear-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms

11 citations · 41 across the 13 of their papers we have counts for

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8 papers · 2 filters

cs.NE2024★ 4 cited

Speeding Up the NSGA-II With a Simple Tie-Breaking Rule

Benjamin Doerr, Tudor Ivan, Martin S. Krejca

The non-dominated sorting genetic algorithm~II (NSGA-II) is the most popular multi-objective optimization heuristic. Recent mathematical runtime analyses have detected two shortcom…

cs.NE2024★ 4 cited

Runtime Analysis for Multi-Objective Evolutionary Algorithms in Unbounded Integer Spaces

Benjamin Doerr, Martin S. Krejca, Günter Rudolph

Randomized search heuristics have been applied successfully to a plethora of problems. This success is complemented by a large body of theoretical results. Unfortunately, the vast…

cs.NE2024★ 8 cited

Difficulties of the NSGA-II with the Many-Objective LeadingOnes Problem

Benjamin Doerr, Dimitri Korkotashvili, Martin S. Krejca

The NSGA-II is the most prominent multi-objective evolutionary algorithm (cited more than 50,000 times). Very recently, a mathematical runtime analysis has proven that this algorit…

cs.NE2024

Evolutionary Algorithms Are Significantly More Robust to Noise When They Ignore It

Denis Antipov, Benjamin Doerr

Randomized search heuristics (RSHs) are known to have a certain robustness to noise. Mathematical analyses trying to quantify rigorously how robust RSHs are to a noisy access to th…

cs.NE2024★ 4 cited

Already Moderate Population Sizes Provably Yield Strong Robustness to Noise

Denis Antipov, Benjamin Doerr, Alexandra Ivanova

Experience shows that typical evolutionary algorithms can cope well with stochastic disturbances such as noisy function evaluations. In this first mathematical runtime analysis of…

cs.NE2024

Proven Runtime Guarantees for How the MOEA/D Computes the Pareto Front From the Subproblem Solutions

Benjamin Doerr, Martin S. Krejca, Noé Weeks

The decomposition-based multi-objective evolutionary algorithm (MOEA/D) does not directly optimize a given multi-objective function , but instead optimizes single-object…

cs.NE2024★ 4 cited

Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy Heuristics

Benjamin Doerr, Martin S. Krejca, Nguyen Vu

The target set selection problem (TSS) asks for a set of vertices such that an influence spreading process started in these vertices reaches the whole graph. The current state of t…

cs.NE2024★ 11 cited

Near-Tight Runtime Guarantees for Many-Objective Evolutionary Algorithms

Simon Wietheger, Benjamin Doerr

Despite significant progress in the field of mathematical runtime analysis of multi-objective evolutionary algorithms (MOEAs), the performance of MOEAs on discrete many-objective p…