Clustering is inherently a difficult problem

with respect to both construction of adequate objective functions and optimization of the objective functions.In this paper

we propose a novel objective function called the Fuzzy Weighted Sum Validity Function (FWSVF)

which is a merged weight from the several fuzzy cluster validity functions

including XB

PE

PC and PBMF.The new validity function has more efficient quality than old ones.Furthermore

we present a Mixed Strategy Evolutionary Clustering Algorithm (MSECA)

which is merged from Mixed Strategy Evolutionary Algorithm and Fuzzy C-means Algorithm and could be applied to optimization of FWSVF. The improved validity function could improve the confidence of clustering solutions and achieve more accurate and robust results.Moreover

MSECA could automatically evolve the proper number of clusters as well as appropriate partitions of the data set

and avoid local optimum.In the experiments

we show the effectiveness of MSECA.In comparison with other genetic clustering algorithms

the MSECA can consistently and efficiently converge to the best known optimum corresponding to given data in concurrence with the convergence result.