This paper presents a simulation framework for multiple stereo camera placement. Multiple stereo camera systems are becoming increasingly popular these days. Applications of multiple stereo camera systems such as tele-immersive systems enable cloning of dynamic scenes in real-time and delivering 3D information from multiple geographic locations to everyone for viewing it in virtual (immersive) 3D spaces. In order to make such multi stereo camera systems ubiquitous, solving the problem of optimal deployment (configuration) of 3D imaging components is motivated by the need (a) to create high quality 3D content and (b) to accommodate application specific requirements into optimal deployment without ad-hoc experimentations. One of the configuration parameters is the placement of stereo cameras that a®ects the quality of 3D reconstructions as well as the resolution achieved by the reconstruction. The novelty of our work is in formulating an optimization framework for optimal camera placement using error based objective function and five constraints. We generate an initial solution to the optimization problem using Genetic Algorithms and then refine the solution using Gradient Descent. The algorithm is validated using actual camera placement as well as using simulation results. The results not only show promising features of our optimization approach but also eliminate ad-hoc experimentation of camera placement for each end application where multiple stereo camera systems can be deployed.