In this study we propose a general mathematical algorithm for the
selection of aux- iliary linear operatorĀ ()Ā and initial guessĀ 0(), which
are the principal parts of Homotopy methods: Homotopy Perturbation
Method (HPM) and Homotopy Anal- ysis Method (HAM). We assume the
coefficients of derivatives involved inĀ ()Ā as a functions of auxiliary
roots ofĀ () = 0. Based on the residual error minimization we compute
unknown roots and thereby obtain the best fitted optimal linear
operator. Additionally, from the efficiency standpoint, we suggest
discretize the exact square residual using the SimsonāsĀ 31Ā algorithm. We
applied our algorithms to six nonlin- ear problems: (i) two nonlinear
initial value problem (IVP) (ii) two highly nonlinear BVPs with
quadratic and cubic nonlinearity, (iii) Bessel equation of zero-order
and (iv) A singular and highly nonlinear BVP (for fluid
electrohydrodynamics). We then compare our techniqueās accuracy and
efficiency to other existing analytical and nu- merical methods. It
demonstrates that our best fitted optimal linear operator is much more
efficient, important (than the artificial controlling parameters or
functions of optimal HAM) and self-sufficient for the convergence of
series solutions over the whole domain, specially for IVP. Also, an
effort is made to search the bestĀ ()Ā for different choices of real roots
and by means of fastest converges of the solution. Our approach is more
effective, straightforward and easy to use when applied to many
nonlinear problems arises in science and engineering, and using our
propose ap- proach homotopy methods (HAM and HPM) will be more powerful.