2016
DOI: 10.1007/s12293-015-0175-9
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A multi-objective memetic algorithm based on decomposition for big optimization problems

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Cited by 40 publications
(6 citation statements)
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References 30 publications
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“…e reconstruction of gene regulatory network based on expression data is also called reverse engineering or network inference. In recent years, various algorithms have been proposed by analysing gene expression data, such as GA [10], gene programming [11], evolutionary strategies [12], and ACO [13]. However, the GRNs modeled by the above algorithm consist of only a limited number of genes.…”
Section: Related Workmentioning
confidence: 99%
“…e reconstruction of gene regulatory network based on expression data is also called reverse engineering or network inference. In recent years, various algorithms have been proposed by analysing gene expression data, such as GA [10], gene programming [11], evolutionary strategies [12], and ACO [13]. However, the GRNs modeled by the above algorithm consist of only a limited number of genes.…”
Section: Related Workmentioning
confidence: 99%
“…In many cases, using the local search procedure enhances [21] the algorithm's efficiency by incorporating specific knowledge about the task to be solved. In recent years, many novel applications of memetic algorithms have been proposed, especially in the area of solving complex optimization problems [22]. Such algorithms aim at solving the shortest path routing problem [23], minimum dominating set problem [24], minimum graph cutwidth problem [25], etc.…”
Section: Formal Definition Of the Task Of Providing Group Anonymitymentioning
confidence: 99%
“…Zhang ve arkadaşları tarafından yapılan çaprazlama ve mutasyon operatörlerini yeniden modelleyerek yeni bir popülasyon bazlı teknik sundukları çalışma sinyal ayrıştırma tabanlı büyük veri problemlerini meta-sezgisel olarak çözen ilk çalışmalardandır [8]. Ayrıca bu çalışmalarını gradyan tabanlı yerel arama yöntemi ve sinyal ayrıştırma kullanarak iyileştirmişler, MOME/D olarak adlandırılan çok amaçlı ayrıştırmalı memetik algoritmayı sunmuşlardır [9]. Geliştirdikleri bu yöntem EEG sinyalleri temelli büyük veri optimizasyon problemlerinde Genetik Algoritma (GA) ve Diferansiyel Gelişim (DE) algoritmalarından daha başarılı sonuçlar ortaya koymuştur.…”
Section: Introductionunclassified