Determining the optimal conditions that lead to desired outcomes (in terms of maximizing the useful products and minimizing the losses) is of outmost importance from both economical and engineering points of view, as it leads to the reduction of consumed resources (time, materials) and of specialized personnel. In this work, two bio-inspired metaheuristic algorithms (Differential Evolution -DE- and Differential Search -DS-) are used to determine the optimal process parameters that lead to a maximum adsorption rate of bromocresol green onto activated carbon. DE is inspired by the Darwinian principle of evolution and DS is based on the Brownian motion of animals. In order to reach the optimization objective, first, a series of experiments were performed by varying the adsorbent quantity, contact time and initial bromocresol green concentration using an experimental plan developed based on Design of Experiments (DOE) approach. After that, the Response Surface Model (RSM) was applied to the gathered data in order to generate a regression equation that describes the relation between the process parameters and efficiency. This relation was then used by the two algorithms to determine the combinations of conditions reactions that generate the highest efficiency. In addition, the Minitab software that generated the responses for DOE and RSM approaches was also used for the process optimization. A comparison between the responses generated by Minitab, DE and DS are provided in Table 1.