The physical models that evolve over time, commonly referred to as evolution equations, have been a crucial component of the mathematical description of complex phenomena. Nonlinear evolution equations (NEEs) arise in a vast assortment of elds, ranging from the physical sciences including thermodynamics, soil mechanics, civil engineering, and non-Newtonian uids to the natural sciences including population ecology, infectious disease epidemiology, and neural networks, etc. Thus, throughout the past few decades, a particular attention has been given to the problem of nding exact solutions of NEEs. By virtue of these solutions, one may give better insight into the physical aspects of the nonlinear models studied. Among the others, certain special form solutions of NEEs may depend only on a single combination of the so-called traveling wave variables because such equations are often described by wave phenomena. Not all equations are solvable. To carry out the integration of NEEs in terms of analytic solutions, a considerable number of analytic methods have been successfully established and developed on this direction; just to mention a few, the Painleve expansion method [1], inverse scattering method [2], Hirota's bilinear method [3], transformed rational function method [4], symmetry method [5], tanh function method [6], homogeneous balance method [7], F-expansion method [8], (G′/G)-expansion method [9], exp-function method [10], homotopy perturbation method [11], the solitary wave ansatz method [12], further improved F-expansion method [13], multiple exp-function method [14], Adomian Pade technique [15], etc. More lately, the superposition principle was successfully used to nd exponential traveling wave solutions to the Hirota bilinear equations [16]. But, it is usually hard and time consuming to tackle various kinds of nonlinear problems via the well-known traditional approaches because they are usually restricted and cannot be im-