Abstract
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
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