Equal size lot streaming to job-shop scheduling problem using genetic algorithms

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

17 Citations (Scopus)

Abstract

A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution. 

LanguageEnglish
Title of host publicationProceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004
Place of PublicationNew York
PublisherIEEE
Pages472-476
Number of pages5
ISBN (Print)0780386353
DOIs
Publication statusPublished - 1 Dec 2004

Fingerprint

Genetic algorithms
Processing
Costs
Job shop scheduling

Keywords

  • lot sizing
  • genetic algorithms
  • job shop scheduling
  • just-in-time
  • lot streaming

Cite this

Chan, F. T. S., Wong, T. C., & Chan, L. Y. (2004). Equal size lot streaming to job-shop scheduling problem using genetic algorithms. In Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004 (pp. 472-476). New York: IEEE. https://doi.org/10.1109/ISIC.2004.1387729
Chan, F. T. S. ; Wong, T. C. ; Chan, L. Y. / Equal size lot streaming to job-shop scheduling problem using genetic algorithms. Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004. New York : IEEE, 2004. pp. 472-476
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abstract = "A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution. ",
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Chan, FTS, Wong, TC & Chan, LY 2004, Equal size lot streaming to job-shop scheduling problem using genetic algorithms. in Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004. IEEE, New York, pp. 472-476. https://doi.org/10.1109/ISIC.2004.1387729

Equal size lot streaming to job-shop scheduling problem using genetic algorithms. / Chan, F. T. S.; Wong, T. C.; Chan, L. Y.

Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004. New York : IEEE, 2004. p. 472-476.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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T1 - Equal size lot streaming to job-shop scheduling problem using genetic algorithms

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N2 - A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution. 

AB - A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution. 

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Chan FTS, Wong TC, Chan LY. Equal size lot streaming to job-shop scheduling problem using genetic algorithms. In Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004. New York: IEEE. 2004. p. 472-476 https://doi.org/10.1109/ISIC.2004.1387729