Many processing techniques have been developed successfully to manufacture metal matrix composites on the commercial scale. The most simplified approach to develop near net shaped aluminum based composites is by liquid metallurgy route as it is economical and can result in mass production. This research focuses on the performance of NN-FPSO for optimization of the parameters in processing metal matrix composites. The concept of the near-neighbor effect is integrated into the force-imitated mechanism and then applied into the PSO algorithm to improve its ability of locating multiple optima on MOPs. In this approach, a new information-sharing scheme is adopted. Each particle iteratively samples a region conducted by a compound acceleration vector, which is composed of the difference between the particle and its personal best position, attraction acceleration, and repulsion acceleration. (C) 2013 Elsevier B.V. All rights reserved.