Co-evolutionary genetic algorithms for reactive scheduling*

Yoshitaka Tanimizu; Yusuke Komatsu; Chisato Ozawa; Koji Iwamura; Nobuhiro Sugimura

doi:10.1299/jamdsm.4.569

Co-evolutionary genetic algorithms for reactive scheduling*

Yoshitaka Tanimizu^*, Yusuke Komatsu, Chisato Ozawa, Koji Iwamura, Nobuhiro Sugimura

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

Previous researches provided a reactive scheduling method using a genetic algorithm to improve disturbed production schedules, due to unexpected disruptions, such as delays of manufacturing operations. This paper deals with an extension of the reactive scheduling method to modify not only the loading sequences but also machining sequences of jobs by using a co-evolutionary genetic algorithm. Two different kinds of individuals for the loading sequences and the machining sequences are generated and improved in co-evolutionary processes. A prototype of new reactive scheduling system was developed, and the effectiveness of the proposed method was verified through computational experiments.

Original language	English
Pages (from-to)	569-577
Number of pages	9
Journal	Journal of Advanced Mechanical Design, Systems and Manufacturing
Volume	4
Issue number	3
DOIs	https://doi.org/10.1299/jamdsm.4.569
Publication status	Published - 2010
Externally published	Yes

Keywords

Co-evolution
Genetic algorithm
Process planning and scheduling
Reactive scheduling

ASJC Scopus subject areas

Mechanical Engineering
Industrial and Manufacturing Engineering

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10.1299/jamdsm.4.569

Cite this

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AU - Ozawa, Chisato

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AU - Sugimura, Nobuhiro

PY - 2010

Y1 - 2010

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AB - Previous researches provided a reactive scheduling method using a genetic algorithm to improve disturbed production schedules, due to unexpected disruptions, such as delays of manufacturing operations. This paper deals with an extension of the reactive scheduling method to modify not only the loading sequences but also machining sequences of jobs by using a co-evolutionary genetic algorithm. Two different kinds of individuals for the loading sequences and the machining sequences are generated and improved in co-evolutionary processes. A prototype of new reactive scheduling system was developed, and the effectiveness of the proposed method was verified through computational experiments.

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KW - Genetic algorithm

KW - Process planning and scheduling

KW - Reactive scheduling

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Co-evolutionary genetic algorithms for reactive scheduling*

Abstract

Keywords

ASJC Scopus subject areas

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