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A genetic algorithm for solving an assembly sequence problem

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A genetic algorithm for solving an assembly sequence problem. / Alharbi, Fawaz Saad; Wang, Qian.

In: Applied Mechanics and Materials, Vol. 872, 10.2017, p. 420-424.

Research output: Contribution to journalArticlepeer-review

Harvard

Alharbi, FS & Wang, Q 2017, 'A genetic algorithm for solving an assembly sequence problem', Applied Mechanics and Materials, vol. 872, pp. 420-424. https://doi.org/10.4028/www.scientific.net/AMM.872.420

APA

Alharbi, F. S., & Wang, Q. (2017). A genetic algorithm for solving an assembly sequence problem. Applied Mechanics and Materials, 872, 420-424. https://doi.org/10.4028/www.scientific.net/AMM.872.420

Vancouver

Alharbi FS, Wang Q. A genetic algorithm for solving an assembly sequence problem. Applied Mechanics and Materials. 2017 Oct;872:420-424. https://doi.org/10.4028/www.scientific.net/AMM.872.420

Author

Alharbi, Fawaz Saad ; Wang, Qian. / A genetic algorithm for solving an assembly sequence problem. In: Applied Mechanics and Materials. 2017 ; Vol. 872. pp. 420-424.

Bibtex

@article{3ba97a6ef82b4e62b44f58a0931ff2ae,
title = "A genetic algorithm for solving an assembly sequence problem",
abstract = "If a product has more than one component, then it must be assembled. The complexity of assembling a product is often subject to the number of assembly components that lead to possible assembly sequences in various forms. Also, it is widely understood that efficiency of assembling a product by reducing assembly times (therefore costs) is vital particularly for small manufacturing companies to survive in an increasingly competitive market. Ideally, it is helpful for determining an optimal assembly sequence of a product at the early design stage. Nevertheless, it may find inefficient using the heuristic approaches in acquisition of a quick solution in terms of an optimal assembly sequence with a minimal assembly time. By contrast, the study indicates that the genetic algorithm (GA) can be used as a cost-effective way for solving an assembly sequence optimisation problem of a product. This paper presents an investigation into a GA used for solving an assembly sequence problem of a ball pen. The study demonstrates that it can provide a quick solution in obtaining an optimal or near-optimal assembly sequence of the product for a small-sized company.",
author = "Alharbi, {Fawaz Saad} and Qian Wang",
year = "2017",
month = oct,
doi = "10.4028/www.scientific.net/AMM.872.420",
language = "English",
volume = "872",
pages = "420--424",
journal = "Applied Mechanics and Materials",
issn = "1662-7482",
note = "2nd International Conference on Applied Engineering, Materials and Mechanics, ICAEMM 2017 ; Conference date: 14-04-2017 Through 17-04-2017",

}

RIS

TY - JOUR

T1 - A genetic algorithm for solving an assembly sequence problem

AU - Alharbi, Fawaz Saad

AU - Wang, Qian

PY - 2017/10

Y1 - 2017/10

N2 - If a product has more than one component, then it must be assembled. The complexity of assembling a product is often subject to the number of assembly components that lead to possible assembly sequences in various forms. Also, it is widely understood that efficiency of assembling a product by reducing assembly times (therefore costs) is vital particularly for small manufacturing companies to survive in an increasingly competitive market. Ideally, it is helpful for determining an optimal assembly sequence of a product at the early design stage. Nevertheless, it may find inefficient using the heuristic approaches in acquisition of a quick solution in terms of an optimal assembly sequence with a minimal assembly time. By contrast, the study indicates that the genetic algorithm (GA) can be used as a cost-effective way for solving an assembly sequence optimisation problem of a product. This paper presents an investigation into a GA used for solving an assembly sequence problem of a ball pen. The study demonstrates that it can provide a quick solution in obtaining an optimal or near-optimal assembly sequence of the product for a small-sized company.

AB - If a product has more than one component, then it must be assembled. The complexity of assembling a product is often subject to the number of assembly components that lead to possible assembly sequences in various forms. Also, it is widely understood that efficiency of assembling a product by reducing assembly times (therefore costs) is vital particularly for small manufacturing companies to survive in an increasingly competitive market. Ideally, it is helpful for determining an optimal assembly sequence of a product at the early design stage. Nevertheless, it may find inefficient using the heuristic approaches in acquisition of a quick solution in terms of an optimal assembly sequence with a minimal assembly time. By contrast, the study indicates that the genetic algorithm (GA) can be used as a cost-effective way for solving an assembly sequence optimisation problem of a product. This paper presents an investigation into a GA used for solving an assembly sequence problem of a ball pen. The study demonstrates that it can provide a quick solution in obtaining an optimal or near-optimal assembly sequence of the product for a small-sized company.

U2 - 10.4028/www.scientific.net/AMM.872.420

DO - 10.4028/www.scientific.net/AMM.872.420

M3 - Article

VL - 872

SP - 420

EP - 424

JO - Applied Mechanics and Materials

JF - Applied Mechanics and Materials

SN - 1662-7482

T2 - 2nd International Conference on Applied Engineering, Materials and Mechanics

Y2 - 14 April 2017 through 17 April 2017

ER -

ID: 11351925