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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| Format: | Article |
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Elsevier Ltd.
2003
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| Online Access: | http://eprints.utm.my/7530/ http://dx.doi.org/10.1080/0020716031000103358 |
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| _version_ | 1845471825988943872 |
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| author | Hamad, S Sanugi, Bahrom Salleh, Shahruddin Hussain |
| author_facet | Hamad, S Sanugi, Bahrom Salleh, Shahruddin Hussain |
| author_sort | Hamad, S |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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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| format | Article |
| id | my.utm.eprints-7530 |
| institution | Universiti Teknologi Malaysia |
| publishDate | 2003 |
| publisher | Elsevier Ltd. |
| record_format | eprints |
| spelling | my.utm.eprints-75302009-01-08T01:19:19Z http://eprints.utm.my/7530/ A neural network model for the common due date job scheduling on unrelated parallel machines Hamad, S Sanugi, Bahrom Salleh, Shahruddin Hussain QA75 Electronic computers. Computer science 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. Elsevier Ltd. 2003-07 Article PeerReviewed Hamad, S and Sanugi, Bahrom and Salleh, Shahruddin Hussain (2003) A neural network model for the common due date job scheduling on unrelated parallel machines. International Journal of Computer Mathematics, 80 (7). pp. 845-851. http://dx.doi.org/10.1080/0020716031000103358 10.1080/0020716031000103358 |
| spellingShingle | QA75 Electronic computers. Computer science Hamad, S Sanugi, Bahrom Salleh, Shahruddin Hussain A neural network model for the common due date job scheduling on unrelated parallel machines |
| title | A neural network model for the common due date job scheduling on unrelated parallel machines |
| title_full | A neural network model for the common due date job scheduling on unrelated parallel machines |
| title_fullStr | A neural network model for the common due date job scheduling on unrelated parallel machines |
| title_full_unstemmed | A neural network model for the common due date job scheduling on unrelated parallel machines |
| title_short | A neural network model for the common due date job scheduling on unrelated parallel machines |
| title_sort | neural network model for the common due date job scheduling on unrelated parallel machines |
| topic | QA75 Electronic computers. Computer science |
| url | http://eprints.utm.my/7530/ http://dx.doi.org/10.1080/0020716031000103358 |
| url_provider | http://eprints.utm.my/ |