The most commonly used numerical optimization techniques include the methods of Gauss-Newton, Newton-Raphson, gradient methods, including methods of steepest ascent and descent, and Marquardt algorithm. Kumar  has recently proposed a new technique based on optimum exponential regression. Another noniterative procedure proposed in this paper is based on the principle of internal regression. In this paper, we have compared these methods using real data sets.
Kumar, K., & Alsaleh, M. A. (1996). A comparative study for the estimation of parameters in nonlinear models. Applied Mathematics and Computation, 77(2-3), 179-184. https://doi.org/10.1016/S0096-3003(95)00211-1