Abstract
| Language | English |
|---|---|
| Pages | 641-651 |
| Number of pages | 11 |
| Journal | Computers and Industrial Engineering |
| Volume | 57 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Oct 2009 |
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Keywords
- genetic algorithm
- assembly job shop
- lot streaming
- part sharing
- dispatching rules
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An evolutionary algorithm for assembly job shop with part sharing. / Chan, F.T.S.; Wong, T.C.; Chan, L.Y.
In: Computers and Industrial Engineering, Vol. 57, No. 3, 01.10.2009, p. 641-651.Research output: Contribution to journal › Article
TY - JOUR
T1 - An evolutionary algorithm for assembly job shop with part sharing
AU - Chan, F.T.S.
AU - Wong, T.C.
AU - Chan, L.Y.
PY - 2009/10/1
Y1 - 2009/10/1
N2 - Assembly job shop problem (AJSP) is an extension of classical job shop problem (JSP). AJSP first starts with a JSP and appends an assembly stage after job completion. Lot Streaming (LS) technique is defined as the process of splitting lots into sub-lots such that successive operation can be overlapped. In this paper, the previous study of LS to AJSP is extended by allowing part sharing among distinct products. In addition to the use of simple dispatching rules (SDRs), an evolutionary approach with genetic algorithm (GA) is proposed to solve the research problem. A number of test problems were conducted to examine the performance of the proposed algorithm. Computational results suggested that the proposed algorithm can outperform the previous one, and can work well with respect to the objective function. Also, the inherent conflicting relationship between the primary objective and the system measurements can be addressed.
AB - Assembly job shop problem (AJSP) is an extension of classical job shop problem (JSP). AJSP first starts with a JSP and appends an assembly stage after job completion. Lot Streaming (LS) technique is defined as the process of splitting lots into sub-lots such that successive operation can be overlapped. In this paper, the previous study of LS to AJSP is extended by allowing part sharing among distinct products. In addition to the use of simple dispatching rules (SDRs), an evolutionary approach with genetic algorithm (GA) is proposed to solve the research problem. A number of test problems were conducted to examine the performance of the proposed algorithm. Computational results suggested that the proposed algorithm can outperform the previous one, and can work well with respect to the objective function. Also, the inherent conflicting relationship between the primary objective and the system measurements can be addressed.
KW - genetic algorithm
KW - assembly job shop
KW - lot streaming
KW - part sharing
KW - dispatching rules
UR - http://www.scopus.com/inward/record.url?scp=69649105066&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2008.11.017
DO - 10.1016/j.cie.2008.11.017
M3 - Article
VL - 57
SP - 641
EP - 651
JO - Computers and Industrial Engineering
T2 - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
SN - 0360-8352
IS - 3
ER -