An evolutionary algorithm for assembly job shop with part sharing

Felix T.S. Chan; T. C. Wong; L. Y. Chan

doi:10.1016/j.cie.2008.11.017

An evolutionary algorithm for assembly job shop with part sharing

Felix T.S. Chan, T. C. Wong, L. Y. Chan

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

29 Citations (Scopus)

Abstract

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. © 2008 Elsevier Ltd. All rights reserved.

Original language	English
Pages (from-to)	641-651
Journal	Computers and Industrial Engineering
Volume	57
Issue number	3
DOIs	https://doi.org/10.1016/j.cie.2008.11.017
Publication status	Published - Oct 2009

Research Keywords

Assembly job shop
Dispatching rules
Genetic algorithm
Lot streaming
Part sharing

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10.1016/j.cie.2008.11.017

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title = "An evolutionary algorithm for assembly job shop with part sharing",

abstract = "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. {\textcopyright} 2008 Elsevier Ltd. All rights reserved.",

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T1 - An evolutionary algorithm for assembly job shop with part sharing

AU - Chan, Felix T.S.

AU - Wong, T. C.

AU - Chan, L. Y.

PY - 2009/10

Y1 - 2009/10

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. © 2008 Elsevier Ltd. All rights reserved.

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. © 2008 Elsevier Ltd. All rights reserved.

KW - Assembly job shop

KW - Dispatching rules

KW - Genetic algorithm

KW - Lot streaming

KW - Part sharing

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DO - 10.1016/j.cie.2008.11.017

M3 - RGC 21 - Publication in refereed journal

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EP - 651

JO - Computers and Industrial Engineering

JF - Computers and Industrial Engineering

IS - 3

ER -

An evolutionary algorithm for assembly job shop with part sharing

Abstract

Research Keywords

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