Parallel Multi-Island Genetic Algotirth for Sorting Unsigned Genomes by Reversals

Silveira, Lucas Ângelo; Soncco-Álvarez, José Luis; Lima, Thaynara Arielly de; Ayala-Rincón, Maurício

doi:10.1109/cec.2018.8477968

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…Silveira et al [27] proposed HoPIMs for a sequential GA introduced in [28] to solve the unsigned translocation problem. Such PIMs outperformed the accuracy obtained by the GA after careful calibration of the migration and breeding cycle parameters and exploration of a variety of topologies [29], [30]. Further, Silveira et al [10] analyzed synchronous HoPIMs for GA, PSO, and the Social Spider Algorithm (SSA).…”

Section: Related Workmentioning

confidence: 99%

Reconfigurable Heterogeneous Parallel Island Models

Silveira¹,

Lima²,

Ayala-Rincón³

2022

Preprint

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Heterogeneous Parallel Island Models (HePIMs) run different bio-inspired algorithms (BAs) in their islands. From a variety of communication topologies and migration policies finetuned for homogeneous PIMs (HoPIMs), which run the same BA in all their islands, previous work introduced HePIMs that provided competitive quality solutions regarding the best-adapted BA in HoPIMs. This work goes a step forward, maintaining the population diversity provided by HePIMs, and increasing their flexibility, allowing BA reconfiguration on islands during execution: according to their performance, islands may substitute their BAs dynamically during the evolutionary process. Experiments with the introduced architectures (RecHePIMs) were applied to the NP-hard problem of sorting permutations by reversals, using four different BAs, namely, simple Genetic Algorithm (GA), Double-point crossover Genetic Algorithm (GAD), Differential Evolution (DE), and self-adjusting Particle Swarm Optimization (PSO). The results showed that the new reconfigurable heterogeneous models compute better quality solutions than the HePIMs closing the gap with the HoPIM running the best-adapted BA.

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