Island (migration) models: evolutionary algorithms based on punctuated equilibria

Martin, W N; Lienig, Jens; Cohoon, J. McGrath

doi:10.1887/0750306653/b840c15

Cited by 24 publications

(37 citation statements)

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“…Each node has its own (sub)population and runs a separate thread of evolution ( fig. 2), thus conceptually subpopulations 'live' on geographically separated regions [9]. A new operator -migration -controls the process of exchanging individuals between regions.…”

Section: Regional Modelsmentioning

confidence: 99%

Agent-Based Models and Platforms for Parallel Evolutionary Algorithms

Kisiel-Dorohinicki¹

2004

Lecture Notes in Computer Science

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Section: Regional Modelsmentioning

confidence: 99%

Agent-Based Models and Platforms for Parallel Evolutionary Algorithms

Kisiel-Dorohinicki¹

2004

Lecture Notes in Computer Science

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“…The cellular GA is also successfully used in the hybridization models (Martin et al [71]). However, the complexity degree of cellular GA is higher than distributed GA due to the increased size of both its subpopulations and underlying grid system consisted of computer processors.…”

Section: Hybrid and Parallel Search-based Evolutionary Algorithmmentioning

confidence: 99%

A New Genetic Algorithm Methodology for Design Optimization of Truss Structures: Bipopulation-Based Genetic Algorithm with Enhanced Interval Search

Talaslioglu

2009

Modelling and Simulation in Engineering

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A new genetic algorithm (GA) methodology, Bipopulation-Based Genetic Algorithm with Enhanced Interval Search (BGAwEIS), is introduced and used to optimize the design of truss structures with various complexities. The results of BGAwEIS are compared with those obtained by the sequential genetic algorithm (SGA) utilizing a single population, a multipopulation-based genetic algorithm (MPGA) proposed for this study and other existing approaches presented in literature. This study has two goals: outlining BGAwEIS's fundamentals and evaluating the performances of BGAwEIS and MPGA. Consequently, it is demonstrated that MPGA shows a better performance than SGA taking advantage of multiple populations, but BGAwEIS explores promising solution regions more efficiently than MPGA by exploiting the feasible solutions. The performance of BGAwEIS is confirmed by better quality degree of its optimal designations compared to algorithms proposed here and described in literature.

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“…The most popular model of this, the island model, coarsely divides the population into several smaller subpopulations, called demes (Martin et al, 1997). An EA evolves each deme independently, but, periodically, information is exchanged by migrating individuals from one deme to another.…”

Section: Island Modelsmentioning

confidence: 99%