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 .