Abstract :
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
Keywords :
decision support systems; manufacturing data processing; order processing; production engineering computing; adaptive genetic hybrids; global search techniques; hybrid decision support system; local search techniques; manufacturing research; order review-and-release; production performance; production system; Computational modeling; Control systems; Costs; Decision support systems; Genetics; Job production systems; Production systems; Resource management; Testing; Virtual manufacturing; Adaptive genetic hybrids; complex production systems; hybrid decision support systems; order review and release; simulation;