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- W1544484741 abstract "Scheduling techniques have been intensively studied by several research communities and have been applied to a wide range of applications in computer and manufacturing environments. In computer systems, scheduling is an important approach to address real-time constraints associated with a set of computing tasks to be executed on one or several computers. Most of the scheduling problems are NP-hard, which is why heuristic and approximation algorithms must be used for large problems. Obviously these methods are of interest when they provide near optimal solutions with a polynomial computational complexity. This paper presents results for scheduling a set of nonpreemptive tasks by using a Hopfield neural network model. We present in this paper how this approach can solve scheduling problems following the anytime paradigm." @default.
- W1544484741 created "2016-06-24" @default.
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- W1544484741 date "2002-11-19" @default.
- W1544484741 modified "2023-10-16" @default.
- W1544484741 title "Anytime scheduling with neural networks" @default.
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- W1544484741 doi "https://doi.org/10.1109/etfa.1995.496803" @default.
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