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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Seridi, K., Jourdan, L., Talbi, EG. (2013). Multiobjective Path Relinking for Biclustering: Application to Microarray Data. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds) Evolutionary Multi-Criterion Optimization. EMO 2013. Lecture Notes in Computer Science, vol 7811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37140-0_18
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DOI: https://doi.org/10.1007/978-3-642-37140-0_18
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