Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system

Yuanjun Laili; Lin Zhang; Fei Tao

doi:10.1109/IEEM.2011.6118248

Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system

Yuanjun Laili^*
, Lin Zhang
, Fei Tao

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

38 Scopus citations

Abstract

A new manufacturing paradigm, i.e. Cloud Manufacturing (CMfg) has been proposed recently. In order to satisfy high efficiency and low cost collaborative design task scheduling in CMfg, a new energy adaptive immune genetic algorithm (EAIGA) was designed. With the introduction of potential energy storage and detection, the new algorithm can not only improve searching diversity based on immune strategy, but also adaptively adjust the probabilities of crossover and mutation with low time complexity. The experimental results demonstrate that the new algorithm can effectively solving collaborative design task scheduling problem with a good balance between searching diversification and intensification.

Original language	English
Title of host publication	IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
Pages	1912-1916
Number of pages	5
DOIs	https://doi.org/10.1109/IEEM.2011.6118248
State	Published - 2011
Event	IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011 - Singapore, Singapore Duration: 6 Dec 2011 → 9 Dec 2011

Publication series

Name	IEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)	2157-3611
ISSN (Electronic)	2157-362X

Conference

Conference	IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
Country/Territory	Singapore
City	Singapore
Period	6/12/11 → 9/12/11

Keywords

adaptive immune genetic algorithm
Collaborative design task scheduling

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10.1109/IEEM.2011.6118248

Cite this

Laili, Y., Zhang, L., & Tao, F. (2011). Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system. In IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011 (pp. 1912-1916). Article 6118248 (IEEE International Conference on Industrial Engineering and Engineering Management). https://doi.org/10.1109/IEEM.2011.6118248

@inproceedings{18613aae095f4cf7b53b6ad7cbb477c6,

title = "Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system",

abstract = "A new manufacturing paradigm, i.e. Cloud Manufacturing (CMfg) has been proposed recently. In order to satisfy high efficiency and low cost collaborative design task scheduling in CMfg, a new energy adaptive immune genetic algorithm (EAIGA) was designed. With the introduction of potential energy storage and detection, the new algorithm can not only improve searching diversity based on immune strategy, but also adaptively adjust the probabilities of crossover and mutation with low time complexity. The experimental results demonstrate that the new algorithm can effectively solving collaborative design task scheduling problem with a good balance between searching diversification and intensification.",

keywords = "adaptive immune genetic algorithm, Collaborative design task scheduling",

author = "Yuanjun Laili and Lin Zhang and Fei Tao",

year = "2011",

doi = "10.1109/IEEM.2011.6118248",

language = "英语",

isbn = "9781457707391",

series = "IEEE International Conference on Industrial Engineering and Engineering Management",

pages = "1912--1916",

booktitle = "IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011",

note = "IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011 ; Conference date: 06-12-2011 Through 09-12-2011",

}

Laili, Y , Zhang, L & Tao, F 2011, Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system. in IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011., 6118248, IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1912-1916, IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011, Singapore, Singapore, 6/12/11. https://doi.org/10.1109/IEEM.2011.6118248

Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system. / Laili, Yuanjun ; Zhang, Lin ; Tao, Fei.
IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011. 2011. p. 1912-1916 6118248 (IEEE International Conference on Industrial Engineering and Engineering Management).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Zhang, Lin

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N2 - A new manufacturing paradigm, i.e. Cloud Manufacturing (CMfg) has been proposed recently. In order to satisfy high efficiency and low cost collaborative design task scheduling in CMfg, a new energy adaptive immune genetic algorithm (EAIGA) was designed. With the introduction of potential energy storage and detection, the new algorithm can not only improve searching diversity based on immune strategy, but also adaptively adjust the probabilities of crossover and mutation with low time complexity. The experimental results demonstrate that the new algorithm can effectively solving collaborative design task scheduling problem with a good balance between searching diversification and intensification.

AB - A new manufacturing paradigm, i.e. Cloud Manufacturing (CMfg) has been proposed recently. In order to satisfy high efficiency and low cost collaborative design task scheduling in CMfg, a new energy adaptive immune genetic algorithm (EAIGA) was designed. With the introduction of potential energy storage and detection, the new algorithm can not only improve searching diversity based on immune strategy, but also adaptively adjust the probabilities of crossover and mutation with low time complexity. The experimental results demonstrate that the new algorithm can effectively solving collaborative design task scheduling problem with a good balance between searching diversification and intensification.

KW - adaptive immune genetic algorithm

KW - Collaborative design task scheduling

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SN - 9781457707391

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Laili Y , Zhang L , Tao F. Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system. In IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011. 2011. p. 1912-1916. 6118248. (IEEE International Conference on Industrial Engineering and Engineering Management). doi: 10.1109/IEEM.2011.6118248

Energy adaptive immune genetic algorithm for collaborative design task scheduling in cloud manufacturing system

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