The present survey provides the state-of-the-art of research, copiously devoted to Evolutionary Approach
(EAs) for clustering exemplified with a diversity of evolutionary computations. The Survey provides a
nomenclature that highlights some aspects that are very important in the context of evolutionary data
clustering. The paper missions the clustering trade-offs branched out with wide-ranging Multi Objective
Evolutionary Approaches (MOEAs) methods. Finally, this study addresses the potential challenges of
MOEA design and data clustering, along with conclusions and recommendations for novice and
researchers by positioning most promising paths of future research.