Lot splitting under different job shop conditions

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

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

6 Citations (Scopus)

Abstract

Lot splitting is defined as the process of splitting lots into smaller sub-lots such that successive operations of the same lot can be overlapped on distinct machines. Hence, the lead time of the lot can be possibly shortened. In this paper, a genetic algorithm-based approach is proposed to examine the lot splitting effect under different job shop conditions as defined by three parameters: processing time range, setup time and system congestion index. The experimental results suggest that lot splitting technique has a significant impact on job shop system with longer processing time and less due date tightness.
Original languageEnglish
Title of host publicationCEC 2007 IEEE Congress on Evolutionary Computation
PublisherIEEE
Pages4722-4728
Number of pages7
ISBN (Print)9781424413393
DOIs
Publication statusPublished - 1 Jan 2007
EventCEC 2007. IEEE Congress on Evolutionary Computation - Singapore, Singapore
Duration: 25 Sep 200728 Sep 2007

Conference

ConferenceCEC 2007. IEEE Congress on Evolutionary Computation
CountrySingapore
CitySingapore
Period25/09/0728/09/07

Fingerprint

Processing
Genetic algorithms

Keywords

  • lot splitting
  • job shop conditions
  • job shop scheduling
  • genetic algorithm-based approach
  • system congestion index
  • machine intelligence
  • lead time reduction

Cite this

Chan, F. T. S., Wong, T. C., & Chan, L. Y. (2007). Lot splitting under different job shop conditions. In CEC 2007 IEEE Congress on Evolutionary Computation (pp. 4722-4728). IEEE. https://doi.org/10.1109/CEC.2007.4425091
Chan, F.T.S. ; Wong, T.C. ; Chan, L.Y. / Lot splitting under different job shop conditions. CEC 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. pp. 4722-4728
@inproceedings{a68de972691f41b1ba9db1593574c9e8,
title = "Lot splitting under different job shop conditions",
abstract = "Lot splitting is defined as the process of splitting lots into smaller sub-lots such that successive operations of the same lot can be overlapped on distinct machines. Hence, the lead time of the lot can be possibly shortened. In this paper, a genetic algorithm-based approach is proposed to examine the lot splitting effect under different job shop conditions as defined by three parameters: processing time range, setup time and system congestion index. The experimental results suggest that lot splitting technique has a significant impact on job shop system with longer processing time and less due date tightness.",
keywords = "lot splitting, job shop conditions, job shop scheduling , genetic algorithm-based approach, system congestion index, machine intelligence, lead time reduction",
author = "F.T.S. Chan and T.C. Wong and L.Y. Chan",
year = "2007",
month = "1",
day = "1",
doi = "10.1109/CEC.2007.4425091",
language = "English",
isbn = "9781424413393",
pages = "4722--4728",
booktitle = "CEC 2007 IEEE Congress on Evolutionary Computation",
publisher = "IEEE",

}

Chan, FTS, Wong, TC & Chan, LY 2007, Lot splitting under different job shop conditions. in CEC 2007 IEEE Congress on Evolutionary Computation. IEEE, pp. 4722-4728, CEC 2007. IEEE Congress on Evolutionary Computation, Singapore, Singapore, 25/09/07. https://doi.org/10.1109/CEC.2007.4425091

Lot splitting under different job shop conditions. / Chan, F.T.S.; Wong, T.C.; Chan, L.Y.

CEC 2007 IEEE Congress on Evolutionary Computation. IEEE, 2007. p. 4722-4728.

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

TY - GEN

T1 - Lot splitting under different job shop conditions

AU - Chan, F.T.S.

AU - Wong, T.C.

AU - Chan, L.Y.

PY - 2007/1/1

Y1 - 2007/1/1

N2 - Lot splitting is defined as the process of splitting lots into smaller sub-lots such that successive operations of the same lot can be overlapped on distinct machines. Hence, the lead time of the lot can be possibly shortened. In this paper, a genetic algorithm-based approach is proposed to examine the lot splitting effect under different job shop conditions as defined by three parameters: processing time range, setup time and system congestion index. The experimental results suggest that lot splitting technique has a significant impact on job shop system with longer processing time and less due date tightness.

AB - Lot splitting is defined as the process of splitting lots into smaller sub-lots such that successive operations of the same lot can be overlapped on distinct machines. Hence, the lead time of the lot can be possibly shortened. In this paper, a genetic algorithm-based approach is proposed to examine the lot splitting effect under different job shop conditions as defined by three parameters: processing time range, setup time and system congestion index. The experimental results suggest that lot splitting technique has a significant impact on job shop system with longer processing time and less due date tightness.

KW - lot splitting

KW - job shop conditions

KW - job shop scheduling

KW - genetic algorithm-based approach

KW - system congestion index

KW - machine intelligence

KW - lead time reduction

UR - http://www.scopus.com/inward/record.url?scp=77951473961&partnerID=8YFLogxK

U2 - 10.1109/CEC.2007.4425091

DO - 10.1109/CEC.2007.4425091

M3 - Conference contribution book

SN - 9781424413393

SP - 4722

EP - 4728

BT - CEC 2007 IEEE Congress on Evolutionary Computation

PB - IEEE

ER -

Chan FTS, Wong TC, Chan LY. Lot splitting under different job shop conditions. In CEC 2007 IEEE Congress on Evolutionary Computation. IEEE. 2007. p. 4722-4728 https://doi.org/10.1109/CEC.2007.4425091