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

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

doi:10.1109/ISIC.2004.1387729

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

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

Design, Manufacturing And Engineering Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

22 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.

Original language	English
Title of host publication	Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004
Place of Publication	New York
Publisher	IEEE
Pages	472-476
Number of pages	5
ISBN (Print)	0780386353
DOIs	https://doi.org/10.1109/ISIC.2004.1387729
Publication status	Published - 1 Dec 2004

Keywords

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

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10.1109/ISIC.2004.1387729

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title = "Equal size lot streaming to job-shop scheduling problem using genetic algorithms",

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. ",

keywords = "lot sizing, genetic algorithms, job shop scheduling, just-in-time, lot streaming",

author = "Chan, {F. T. S.} and Wong, {T. C.} and Chan, {L. Y.}",

year = "2004",

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doi = "10.1109/ISIC.2004.1387729",

language = "English",

isbn = "0780386353",

pages = "472--476",

booktitle = "Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004",

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TY - GEN

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

AU - Chan, F. T. S.

AU - Wong, T. C.

AU - Chan, L. Y.

PY - 2004/12/1

Y1 - 2004/12/1

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.

KW - lot sizing

KW - genetic algorithms

KW - job shop scheduling

KW - just-in-time

KW - lot streaming

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U2 - 10.1109/ISIC.2004.1387729

DO - 10.1109/ISIC.2004.1387729

M3 - Conference contribution book

AN - SCOPUS:20344394416

SN - 0780386353

SP - 472

EP - 476

BT - Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004

PB - IEEE

CY - New York

ER -

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

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Keywords

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