Over recent years order review and release (ORR) has attracted increasing attention in manufacturing research due to its important impact on production performance. By means of effectively controlling the rate of input of jobs into the production system, in fact, the sustainability of feasible and economical production levels can be significantly enhanced. In this context of research the paper proposes a hybrid decision support system (DSS) to address the simultaneous review of multiple incoming orders and, thereby, support better informed acceptance and rejection decisions. The DSS, as developed for this research, relies on the interactive use of simulation and adaptive genetic hybrids, integrating local and global search techniques, to identify the combination of accepted orders that maximizes production performance while reducing the risk of accepting sub-optimal combinations