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2001

Using simulation and neural networks to develop a scheduling advisor

12 years 3 months ago
Using simulation and neural networks to develop a scheduling advisor
The research using artificial intelligence and computer simulation introduces a new approach for solving the job shop-scheduling problem. The new approach is based on the development of a neural network-scheduling advisor, which is trained using optimal scheduling decisions. The data set, which is used to train the neural network, is obtained from simulation experiments with small-scale job shop scheduling problems. The paper formulates the problem and after a review of the current solution methods it describes the steps of a new methodology for developing the neural network-scheduling advisor and collecting the data required for its training. The paper concludes by mentioning the expected findings that can be used to evaluate the degree of success of the new methodology.
Thanos Alifantis, Stewart Robinson
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where WSC
Authors Thanos Alifantis, Stewart Robinson
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