The application of lot streaming to assembly job shop under resource constraints

Tung Sun Chan; T. C. Wong; P. L.Y. Chan

doi:10.3182/20080706-5-KR-1001.1142

The application of lot streaming to assembly job shop under resource constraints

Tung Sun Chan, T. C. Wong, P. L.Y. Chan

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (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 will be extended by introducing resource constraints. To reduce the computational effort, we propose a new Genetic Algorithm (GA) approach which is the modification of the algorithm in our previous paper. A number of test problems are conducted to examine the performance of the new GA approach. Moreover, the single GA approach will be compared with a single Particle Swarm Optimization (PSO) approach. Computational results suggest that the new algorithm can outperform the previous one and the PSO approach with respect to the objective function.

Original language	English
Title of host publication	Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
Volume	17
Edition	1 PART 1
DOIs	https://doi.org/10.3182/20080706-5-KR-1001.1142
Publication status	Published - 1 Dec 2008
Event	17th World Congress, International Federation of Automatic Control, IFAC - Seoul, Korea, Republic of Duration: 6 Jul 2008 → 11 Jul 2008

Conference

Conference	17th World Congress, International Federation of Automatic Control, IFAC
Country/Territory	Korea, Republic of
City	Seoul
Period	6/07/08 → 11/07/08

Keywords

Assembly and disassembly
Job and activity scheduling
Manufacturing plant control

ASJC Scopus subject areas

Control and Systems Engineering

More information

10.3182/20080706-5-KR-1001.1142

Cite this

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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 will be extended by introducing resource constraints. To reduce the computational effort, we propose a new Genetic Algorithm (GA) approach which is the modification of the algorithm in our previous paper. A number of test problems are conducted to examine the performance of the new GA approach. Moreover, the single GA approach will be compared with a single Particle Swarm Optimization (PSO) approach. Computational results suggest that the new algorithm can outperform the previous one and the PSO approach with respect to the objective function.",

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Chan, TS, Wong, TC & Chan, PLY 2008, The application of lot streaming to assembly job shop under resource constraints. in Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC. 1 PART 1 edn, vol. 17, 17th World Congress, International Federation of Automatic Control, IFAC, Seoul, Korea, Republic of, 6/07/08. https://doi.org/10.3182/20080706-5-KR-1001.1142

The application of lot streaming to assembly job shop under resource constraints. / Chan, Tung Sun; Wong, T. C.; Chan, P. L.Y.
Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC. Vol. 17 1 PART 1. ed. 2008.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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T1 - The application of lot streaming to assembly job shop under resource constraints

AU - Chan, Tung Sun

AU - Wong, T. C.

AU - Chan, P. L.Y.

PY - 2008/12/1

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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 will be extended by introducing resource constraints. To reduce the computational effort, we propose a new Genetic Algorithm (GA) approach which is the modification of the algorithm in our previous paper. A number of test problems are conducted to examine the performance of the new GA approach. Moreover, the single GA approach will be compared with a single Particle Swarm Optimization (PSO) approach. Computational results suggest that the new algorithm can outperform the previous one and the PSO approach with respect to the objective function.

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BT - Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC

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The application of lot streaming to assembly job shop under resource constraints

Abstract

Conference

Keywords

ASJC Scopus subject areas

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