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Virtual Manufacturing Cell Design Using a PSO Approach with Alternative Neighbourhood Topologies

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Simulated Evolution and Learning (SEAL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6457))

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Abstract

In this paper an application of conventional Particle Swarm Optimization (PSO) approach with alternative neighborhood topologies is proposed for the design of virtual manufacturing cells within which machines and jobs are assigned to the cells with a view to maximize productive output, whilst simultaneously minimizing the inter-cell movements due to the limited availability of machines. The PSO results are then compared with the following approaches: Binary PSO (BPSO) and Preemptive / Lexico Goal Programming. It is observed that the PSO topological variants perform well for the assumed VCM design problem.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, India

    Rahul Caprihan

  2. Faculty of Business & Economics, University of Groningen, Groningen, The Netherlands

    Jannes Slomp

  3. Faculty of Science, Dayalbagh Educational Institute, Dayalbagh, Agra, India

    Gursaran Srivastava

  4. Dynamic Pistons Ltd., Agra, India

    Khushboo Agarwal

Authors
  1. Rahul Caprihan
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  2. Jannes Slomp
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  3. Gursaran Srivastava
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  4. Khushboo Agarwal
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Kalyanmoy Deb

  2. Department of Computer Science andl Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Arnab Bhattacharya

  3. Department of Metallurgical and Materials Engineering, Indian Institute of Technology Kharagpur, 712302, Kharagpur, West Bengal, India

    Nirupam Chakraborti

  4. Department of Civil Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Partha Chakroborty  & Ashu Jain  & 

  5. Department of Electronics and Communication Engineering, Jadavpur University, 700032, Kolkata, West Bengal, India

    Swagatam Das

  6. Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Joydeep Dutta

  7. Department of Chemical Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, Uttar Pradesh, India

    Santosh K. Gupta

  8. Aspiring Minds, 24 Pusa Road, 110005, New Delhi, India

    Varun Aggarwal

  9. Warwick Business School, University of Warwick, CV4 7AL, Coventry, UK

    Jürgen Branke

  10. Department of Computer Science and Engineering, University of Nevada, 89557, Reno, NV, USA

    Sushil J. Louis

  11. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore

    Kay Chen Tan

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© 2010 Springer-Verlag Berlin Heidelberg

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Caprihan, R., Slomp, J., Srivastava, G., Agarwal, K. (2010). Virtual Manufacturing Cell Design Using a PSO Approach with Alternative Neighbourhood Topologies. In: Deb, K., et al. Simulated Evolution and Learning. SEAL 2010. Lecture Notes in Computer Science, vol 6457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17298-4_74

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  • DOI: https://doi.org/10.1007/978-3-642-17298-4_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17297-7

  • Online ISBN: 978-3-642-17298-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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