Development of a Genetic Algorithm for Optimization of Nanoalloys

Lloyd, Lesley D.; Johnston, Roy L.; Salhi, Saïd

doi:10.1007/978-3-540-24855-2_144

Cited by 4 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The studies reported here and previously in the literature14, 25, 33 confirm that the GA is a powerful technique for finding (with a high probability) the global minimum in cluster geometry optimization. Biasing the population by seeding with certain suboptimal local minima and/or predating other local minima has produced a more robust algorithm.…”

Section: Discussionsupporting

confidence: 82%

See 1 more Smart Citation

Strategies for increasing the efficiency of a genetic algorithm for the structural optimization of nanoalloy clusters

2005

Self Cite

View full text Add to dashboard Cite

An improved genetic algorithm (GA) is described that has been developed to increase the efficiency of finding the global minimum energy isomers for nanoalloy clusters. The GA is optimized for the example Pt12Pd12, with specific investigation of: the effect of biasing the initial population by seeding; the effect of removing specified clusters from the population ("predation"); and the effect of varying the type of mutation operator applied. These changes are found to significantly enhance the efficiency of the GA, which is subsequently demonstrated by the application of the best strategy to a new cluster, namely Pt19Pd19.

show abstract

Section: Discussionsupporting

confidence: 82%

“…It should be mentioned that this method is related, but not identical to, Tabu Search. Tabu Search is a deterministic and aggressive search method based on temporarily stopping reversal moves from occurring to avoid cycling,32, 33 whereas our predation strategy removes the isomer permanently.…”

Section: Resultsmentioning

confidence: 99%