Air flow rate (VVM) and stirring rate (RPM) were optimized to maximize the production of an antibiotic, Actinomycin D, from a mutant of Streptomyces sindenensis-M-46. Experiments were conducted using the central composite design (CCD), A Response surface polynomial equation was used to establish a mathematical relationship between the inputs (air flow rate and stirring rate) and targets (Antibiotic concentration after 5 days of incubation, from CCD). Genetic Algorithm (GA) and Nelder-Mead downhill simplex (NMDS) were separately used to optimize the fermentation parameters for maximum antibiotic production. Both GA and NMDS predicted an almost similar optimum combination of fermentation parameters. Antibiotic concentration increased by almost 55% as compared to the maximum obtained at the optimum point in shake flask experiment (1.26 to ~2 gm/L). The polynomial equation was also used to construct a response surface showing the effect of fermentation parameters on antibiotic yield. The response equation successfully predicted the effect of individual fermentation parameters (varying one at a time) on antibiotic yield. Efficient oxygen mass transfer conditions appear to be an important factor governing antibiotic yield.