Abstract
The main contribution of this paper is the development of a multi-objective FMS scheduler which is designed to maximally satisfy the desired values of multiple objectives set by the operator. For each production interval, a decision rule for each decision variable is chosen by the FMS scheduler. A competitive neural network is applied to present fast but good decision rules to the operator. A unique feature of the FMS scheduler is that the competitive neural network generates the next decision rules based on the current decision rules, system status and performance measures. A commercial FMS is simulated to prove the effectiveness of the FMS scheduler. The result shows that the FMS scheduler can successfully satisfy multiple objectives.
| Original language | English |
|---|---|
| Pages (from-to) | 1749-1765 |
| Number of pages | 17 |
| Journal | International Journal of Production Research |
| Volume | 36 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 1998 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
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A competitive neural network approach to multi-objective FMS scheduling. / Min, H. S.; Yih, Y.; Kim, C. O.
In: International Journal of Production Research, Vol. 36, No. 7, 01.01.1998, p. 1749-1765.Research output: Contribution to journal › Article
TY - JOUR
T1 - A competitive neural network approach to multi-objective FMS scheduling
AU - Min, H. S.
AU - Yih, Y.
AU - Kim, C. O.
PY - 1998/1/1
Y1 - 1998/1/1
N2 - The main contribution of this paper is the development of a multi-objective FMS scheduler which is designed to maximally satisfy the desired values of multiple objectives set by the operator. For each production interval, a decision rule for each decision variable is chosen by the FMS scheduler. A competitive neural network is applied to present fast but good decision rules to the operator. A unique feature of the FMS scheduler is that the competitive neural network generates the next decision rules based on the current decision rules, system status and performance measures. A commercial FMS is simulated to prove the effectiveness of the FMS scheduler. The result shows that the FMS scheduler can successfully satisfy multiple objectives.
AB - The main contribution of this paper is the development of a multi-objective FMS scheduler which is designed to maximally satisfy the desired values of multiple objectives set by the operator. For each production interval, a decision rule for each decision variable is chosen by the FMS scheduler. A competitive neural network is applied to present fast but good decision rules to the operator. A unique feature of the FMS scheduler is that the competitive neural network generates the next decision rules based on the current decision rules, system status and performance measures. A commercial FMS is simulated to prove the effectiveness of the FMS scheduler. The result shows that the FMS scheduler can successfully satisfy multiple objectives.
UR - http://www.scopus.com/inward/record.url?scp=0032121915&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0032121915&partnerID=8YFLogxK
U2 - 10.1080/002075498192940
DO - 10.1080/002075498192940
M3 - Article
AN - SCOPUS:0032121915
VL - 36
SP - 1749
EP - 1765
JO - International Journal of Production Research
JF - International Journal of Production Research
SN - 0020-7543
IS - 7
ER -