A neural network model for the common due date job scheduling on unrelated parallel machines
This paper presents an approach for scheduling under a common due date on parallel unrelated machine problems based on artificial neural network. The objective is to allocate and sequence the jobs on the machines so that the total cost is minimized. The total cost is the sum of the total earliness a...
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| Main Authors: | , , |
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| Format: | Article |
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Elsevier Ltd.
2003
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/7530/ http://dx.doi.org/10.1080/0020716031000103358 |
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| Summary: | This paper presents an approach for scheduling under a common due date on parallel unrelated machine problems based on artificial neural network. The objective is to allocate and sequence the jobs on the machines so that the total cost is minimized. The total cost is the sum of the total earliness and the total tardiness cost. The multilayer Perceptron (MLP) neural network is a suitable model in our study due to the fact that the problem is NP-hard. In our study, neural network has been proven to be effective and robust in generating near optimal solutions to the problem.
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