Article

A comparison of messy GA and permutation based GA for job shop scheduling

Authors:

Pio Fenton,

Paul WalshAuthors Info & Claims

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

Pages 1593 - 1594

https://doi.org/10.1145/1068009.1068275

Published: 25 June 2005 Publication History

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Abstract

This paper presents the results of a fair comparison between a messy GA and a permutation based simple GA as applied to a job shop scheduling system. An examination is made at a macro level in terms of performance and quality of schedules achieved and conclusions are drawn as to the superiority of messy GA or otherwise.

References

[1]

www.lancet.mit.edu/ga (accessed 10-January-2005)

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[2]

Dirk Christian Mattfeld, "Evolutionary Search and the Job-Shop: Investigations on Genetic Algorithms for Production Scheduling"1995 Spinger- Verlag

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[3]

Dimitri Knjazew "OmeGa: A competent Genetic Algorithm for Solving Permutation and Scheduling Problems" 2001, Kluwer Academic Press.

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[4]

Muth, J. F. and Thompson, G. L., eds., Industrial Scheduling, Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1963.

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[5]

ta01-ta80 are from É. D. Taillard (1993), "Benchmarks for basic scheduling problems", European Journal of Operational Research 64, Pages 278--28

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Cited By

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Raschip MLuchian HPelikan MBranke J(2010)Using messy genetic algorithms for solving the winner determination problemProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830810(1825-1832)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830810
Yang XZeng JLiang J(2009)Apply Inversion Order Number Genetic Algorithm to the Job Shop Scheduling ProblemProceedings of the 2009 Third International Conference on Genetic and Evolutionary Computing10.1109/WGEC.2009.104(196-200)Online publication date: 14-Oct-2009
https://dl.acm.org/doi/10.1109/WGEC.2009.104
Xi JZhao XZhang XZhang YWang S(2009)The Messy-Niche algorithm used for image super-resolution2009 International Conference on Wireless Communications & Signal Processing10.1109/WCSP.2009.5371522(1-4)Online publication date: Nov-2009
https://doi.org/10.1109/WCSP.2009.5371522
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Index Terms

A comparison of messy GA and permutation based GA for job shop scheduling
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence

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Information

Published In

GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation

June 2005

2272 pages

ISBN:1595930108

DOI:10.1145/1068009

Editor:
Hans-Georg Beyer
Vorarlberg University of Applied Sciences, Austria
,
General Chair:
Una-May O'Reilly
CSAIL, MIT

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2005

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GECCO05

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GECCO05: Genetic and Evolutionary Computation Conference

June 25 - 29, 2005

Washington DC, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

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Raschip MLuchian HPelikan MBranke J(2010)Using messy genetic algorithms for solving the winner determination problemProceedings of the 12th annual conference companion on Genetic and evolutionary computation10.1145/1830761.1830810(1825-1832)Online publication date: 7-Jul-2010
https://dl.acm.org/doi/10.1145/1830761.1830810
Yang XZeng JLiang J(2009)Apply Inversion Order Number Genetic Algorithm to the Job Shop Scheduling ProblemProceedings of the 2009 Third International Conference on Genetic and Evolutionary Computing10.1109/WGEC.2009.104(196-200)Online publication date: 14-Oct-2009
https://dl.acm.org/doi/10.1109/WGEC.2009.104
Xi JZhao XZhang XZhang YWang S(2009)The Messy-Niche algorithm used for image super-resolution2009 International Conference on Wireless Communications & Signal Processing10.1109/WCSP.2009.5371522(1-4)Online publication date: Nov-2009
https://doi.org/10.1109/WCSP.2009.5371522
Shouichi Matsui Seiji Yamada (2007)An empirical performance evaluation of a parameter-free genetic algorithm for job-shop scheduling problem2007 IEEE Congress on Evolutionary Computation10.1109/CEC.2007.4424965(3796-3803)Online publication date: Sep-2007
https://doi.org/10.1109/CEC.2007.4424965

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Heuristic Optimization for Dual-resource Constrained Job Shop Scheduling