Parallel evolutionary algorithms can achieve super-linear performance

DOI10.1016/S0020-0190(01)00281-2zbMath1013.68292OpenAlexW2104805479MaRDI QIDQ1603567

Enrique Alba

Publication date: 14 July 2002

Published in: Information Processing Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0020-0190(01)00281-2

zbMATH Keywords

performance evaluationparallel algorithmsevolutionary algorithmsserial fractionsuper-linear speedup

Mathematics Subject Classification ID

Parallel algorithms in computer science (68W10)

Related Items (9)

ON THE BEHAVIOR OF PARALLEL GENETIC ALGORITHMS FOR OPTIMAL PLACEMENT OF ANTENNAE IN TELECOMMUNICATIONS ⋮ Analysis of speedups in parallel evolutionary algorithms and \((1 + \lambda)\) EAs for combinatorial optimization ⋮ Design and analysis of migration in parallel evolutionary algorithms ⋮ Evaluation of the migrated solutions for distributing reference point-based multi-objective optimization algorithms ⋮ Island models meet rumor spreading ⋮ Distributed estimation of distribution algorithms for continuous optimization: how does the exchanged information influence their behavior? ⋮ A parallel hybrid metaheuristic for bicluster editing ⋮ Self-healing strategies for memetic algorithms in unstable and ephemeral computational environments ⋮ Analysis of distributed genetic algorithms for solving cutting problems

Cites Work

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• Heterogeneous computing and parallel genetic algorithms.
• Anomalies in parallel branch-and-bound algorithms
• Analyzing synchronous and asynchronous parallel distributed genetic algorithms

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