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An Order-Based GA for Robot-Based Assembly Line Balancing Problem

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Proceedings of the Eleventh International Conference on Management Science and Engineering Management (ICMSEM 2017)

Part of the book series: Lecture Notes on Multidisciplinary Industrial Engineering ((LNMUINEN))

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Abstract

In the real world, there are a lot of scenes from which the product is made by using the robot, which needs different assembly times to perform a given task, because of its capabilities and specialization. For a robotic assembly line balancing (rALB) problem, a set of tasks have to be assigned to stations, and each station needs to select one robot to process the assigned tasks. In this paper, we propose a hybrid genetic algorithm (hGA) based on an order encoding method for solving rALB problem. In the hGA, we use new representation method. Advanced genetic operators adapted to the specific chromosome structure and the characteristics of the rALB problem are used. In order to strengthen the search ability, a local search procedure is integrated under the framework the genetic algorithm. Some practical test instances demonstrate the effectiveness and efficiency of the proposed algorithm.

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Acknowledgements

This work is partly supported by the National Natural Science Foundation of China under Grant 61572100, and in part by the Grant-in-Aid for Scientific Research (C) of Japan Society of Promotion of Science (JSPS) No. 15K00357.

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Authors and Affiliations

  1. Dalian University of Technology, Dalian, 116024, People’s Republic of China

    Lin Lin & Chenglin Yao

  2. Fuzzy Logic Systems Institute, Tokyo, Japan

    Lin Lin

  3. Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, 116024, People’s Republic of China

    Lin Lin

  4. Waseda University, Tokyo, 169-0051, Japan

    Xinchang Hao

Authors
  1. Lin Lin
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  2. Chenglin Yao
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  3. Xinchang Hao
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Corresponding author

Correspondence to Lin Lin .

Editor information

Editors and Affiliations

  1. Business and Administration, Sichuan University, Chengdu, China

    Jiuping Xu

  2. Fuzzy Logic Systems Institute, Tokyo University of Science, Tokyo, Tokyo, Japan

    Mitsuo Gen

  3. Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Asaf Hajiyev

  4. Monash University, Clayton, Victoria, Australia

    Fang Lee Cooke

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Lin, L., Yao, C., Hao, X. (2018). An Order-Based GA for Robot-Based Assembly Line Balancing Problem. In: Xu, J., Gen, M., Hajiyev, A., Cooke, F. (eds) Proceedings of the Eleventh International Conference on Management Science and Engineering Management. ICMSEM 2017. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-59280-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-59280-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59279-4

  • Online ISBN: 978-3-319-59280-0

  • eBook Packages: EngineeringEngineering (R0)

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