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An Assembly Sequence Planning Approach with a Multi-state Particle Swarm Optimization

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Trends in Applied Knowledge-Based Systems and Data Science (IEA/AIE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9799))

Abstract

Assembly sequence planning (ASP) becomes one of the major challenges in the product design and manufacturing. A good assembly sequence leads in reducing the cost and time of the manufacturing process. However, assembly sequence planning is known as a classical hard combinatorial optimization problem. Assembly sequence planning with more product components becomes more difficult to be solved. In this paper, an approach based on a new variant of Particle Swarm Optimization Algorithm (PSO) called the multi-state of Particle Swarm Optimization (MSPSO) is used to solve the assembly sequence planning problem. As in of Particle Swarm Optimization Algorithm, MSPSO incorporates the swarming behaviour of animals and human social behaviour, the best previous experience of each individual member of swarm, the best previous experience of all other members of swarm, and a rule which makes each assembly component of each individual solution of each individual member is occurred once based on precedence constraints and the best feasible sequence of assembly is then can be determined. To verify the feasibility and performance of the proposed approach, a case study has been performed and comparison has been conducted against other three approaches based on Simulated Annealing (SA), Genetic Algorithm (GA), and Binary Particle Swarm Optimization (BPSO). The experimental results show that the proposed approach has achieved significant improvement.

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Acknowledgement

This work is financially supported by the Ministry of Higher Education Malaysia through the Fundamental Research Grant Scheme (FRGS) VOT RDU140114 granted to Universiti Malaysia Pahang.

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Authors and Affiliations

  1. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia

    Ismail Ibrahim, Zuwairie Ibrahim & Hamzah Ahmad

  2. Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia

    Zulkifli Md. Yusof

Authors
  1. Ismail Ibrahim
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  2. Zuwairie Ibrahim
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  3. Hamzah Ahmad
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  4. Zulkifli Md. Yusof
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Corresponding author

Correspondence to Zuwairie Ibrahim .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University , Iwate, Japan

    Hamido Fujita

  2. Department Computer Science, Texas State University, San Marcos, Texas, USA

    Moonis Ali

  3. Universiti Teknologi Malaysis (UTM), Bahru, Malaysia

    Ali Selamat

  4. Iwate Prefectural University , Iwate, Japan

    Jun Sasaki

  5. Iwate Prefectural University , Iwate, Japan

    Masaki Kurematsu

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© 2016 Springer International Publishing Switzerland

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Ibrahim, I., Ibrahim, Z., Ahmad, H., Yusof, Z.M. (2016). An Assembly Sequence Planning Approach with a Multi-state Particle Swarm Optimization. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_71

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  • DOI: https://doi.org/10.1007/978-3-319-42007-3_71

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42006-6

  • Online ISBN: 978-3-319-42007-3

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