Abstract
Job-shop scheduling cannot casually be accomplished analytically, so, it is done by computer Simulation using heuristic priority rules. The SLACK rule for calculating the margins of jobs to then due-dates is effective in meeting the due-dates. However, the calculated margins are not precise because the actual margin is shortened due to conflicts with other jobs. The authors proposed a method for estimating the margins by using a neural network It was found that the method is effectivefor improving the average lateness to due-dates but not the maximum lateness, This paper proposes a method for adding a second neural network for judging thereliability of the estimated margins composed to the first one and for switching to the margins calculated by the SLACK rule when the reliability is low. It is verified by scheduling simulations that the proposed method is effective in decreasing the maximum lateness to due-dates as much as the average lateness
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
