Crossover can be constructive when computing unique input-output sequences
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Publication:416273
DOI10.1007/S00500-010-0610-2zbMath1237.68189OpenAlexW1981241191MaRDI QIDQ416273
Publication date: 10 May 2012
Published in: Soft Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00500-010-0610-2
evolutionary algorithmscrossover operatorfinite state machinesruntime analysisunique input-output sequences
Related Items (9)
Tight bounds on the expected runtime of a standard steady state genetic algorithm ⋮ Fixed-parameter tractability of crossover: steady-state GAs on the closest string problem ⋮ Design and analysis of different alternating variable searches for search-based software testing ⋮ An extended jump functions benchmark for the analysis of randomized search heuristics ⋮ On the benefits of populations for the exploitation speed of standard steady-state genetic algorithms ⋮ A study on the extended unique input/output sequence ⋮ Testing restorable systems: formal definition and heuristic solution based on river formation dynamics ⋮ Lower bounds on the runtime of crossover-based algorithms via decoupling and family graphs ⋮ Hitting times of local and global optima in genetic algorithms with very high selection pressure
Cites Work
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- Crossover can provably be useful in evolutionary computation
- Real royal road functions for constant population size
- On the analysis of the \((1+1)\) evolutionary algorithm
- A study of drift analysis for estimating computation time of evolutionary algorithms
- The analysis of evolutionary algorithms -- A proof that crossover really can help
- The one-dimensional Ising model: mutation versus recombination
- Formal Approaches to Software Testing
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