This paper proposes a new clustering method by using genetic algorithms for the optimization of the objective functions in conventional clustering algorithms. Experimental results show that our algorithms have much higher likelihood of finding the global or near global optimum solutionsthan the c-means and the c-lines clustering algorithms.