Parallel continuous optimization methods are motivated here by applications in science and engineering. The key issues are addressed at different computational levels including local and global optimization as well as strategies for large, sparse versus small but expensive problems. Topics covered include global optimization, direct search with and without surrogates, optimization of linked subsystems, and variable and constraint distribution. Finally, there is a discussion of future research directions.