This paper describes a generic neural network scheduler for scheduling a set of jobs with deadlines on a set of resources in critical real time applications, in which a schedule is to be obtained within a short time span. The proposed generic neural network scheduler is based on GENET network model with progressive stochastic search scheme. To cope with the bicriterion of deadlines and optimization, a heuristic policy which is modified from the earliest deadline first policy and an optimal mechanism are embedded into the proposed model. Computer simulations show that the proposed generic neural network scheduler has a promising performance, with regard to the probability of generating a satisfied feasible schedule, compared with a scheduler that executes conventional priority heuristic algorithms.
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