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Multi-objective path relinking for bi-clustering: Application to microarray data

Abstract : In this work we deal with a multiobjective biclustering problem applied to microarray data. MOBI nsga [21] is one of the multiobjective metaheuristics that have been proposed to solve a new multiobjective formulation of the biclustering problem. Using MOBI nsga , biclusters of good quality can be extracted. However, the generated front approximation contains a lot of gaps. Using path relinking strategies, our aim is to improve the generated front’s quality by filling the gaps with new solutions. Therefore, we propose a general scheme PR-MOBI nsga of different possible hybridization of MOBI nsga with path relinking strategies. A comparison of different PR-MOBI nsga hybridizations is performed. Experimental results on reel data sets show that PR-MOBI nsga allows to extract new interesting solutions and to improve the Pareto front approximation generated by MOBI nsga .
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Submitted on : Wednesday, January 21, 2015 - 3:06:18 PM
Last modification on : Tuesday, December 6, 2022 - 12:42:13 PM

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Khedidja Seridi, Laetitia Jourdan, El-Ghazali Talbi. Multi-objective path relinking for bi-clustering: Application to microarray data. EMO 2013 : 7th Int. Conf. On Evolutionary Multi-criterion Optimization, Mar 2014, Sheffield, United Kingdom. pp.200-214, ⟨10.1007/978-3-642-37140-0_18⟩. ⟨hal-01107757⟩



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