Running time analysis of the (1+1)-EA for robust linear optimization
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Publication:2003994
DOI10.1016/j.tcs.2020.07.001zbMath1460.68137arXiv1906.06873OpenAlexW3041825806MaRDI QIDQ2003994
Yang Yu, Chao Qian, Chao Bian, Ke Tang
Publication date: 13 October 2020
Published in: Theoretical Computer Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1906.06873
Analysis of algorithms (68W40) Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Integer programming (90C10) Approximation methods and heuristics in mathematical programming (90C59) Robustness in mathematical programming (90C17)
Cites Work
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- Robustness of populations in stochastic environments
- Runtime analysis of ant colony optimization on dynamic shortest path problems
- Bioinspired computation in combinatorial optimization. Algorithms and their computational complexity
- Analyzing evolutionary algorithms. The computer science perspective.
- Robust optimization - a comprehensive survey
- An efficient constraint handling method for genetic algorithms
- On the analysis of the \((1+1)\) evolutionary algorithm
- Running time analysis of the \((1+1)\)-EA for OneMax and LeadingOnes under bit-wise noise
- Reoptimization time analysis of evolutionary algorithms on linear functions under dynamic uniform constraints
- A simple ant colony optimizer for stochastic shortest path problems
- Multiplicative drift analysis
- Analysis of the \((1 + 1)\) EA on subclasses of linear functions under uniform and linear constraints
- (1+1) EA on Generalized Dynamic OneMax
- Efficient Optimisation of Noisy Fitness Functions with Population-based Evolutionary Algorithms
- Run-Time Analysis of Population-Based Evolutionary Algorithm in Noisy Environments
- Robust Monotone Submodular Function Maximization
- Greed is Good: Algorithmic Results for Sparse Approximation
- Tight Bounds on the Optimization Time of a Randomized Search Heuristic on Linear Functions
- Optimizing expected path lengths with ant colony optimization using fitness proportional update
- Drift analysis and average time complexity of evolutionary algorithms