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Multi-Objective Optimization of Particle Reinforced Silicone Rubber Mould Material for Soft Tooling Process

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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

Multi-objective optimizations of various conflicting objectives in designing particle reinforced silicone rubber are conducted using evolutionary algorithms to reduce the processing time of soft tooling process. A well-established evolutionary algorithm based multi-objective optimization tool, NSGA-II is adopted to find the optimal values of design parameters. From the obtained Pareto-optimal fronts, suitable multi-criterion decision making techniques are used to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of soft tooling process for industrial applications.

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References

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Author information

Authors and Affiliations

  1. Central Mechanical Engineering Research Institute (CSIR), Durgapur, 713209, WB, India

    Arup Kumar Nandi

  2. Birla Institute of Technology, Deoghar Campus Jasidih, Deoghar, 814142, Jharkhand, India

    Shubhabrata Datta

Authors
  1. Arup Kumar Nandi
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  2. Shubhabrata Datta
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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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Nandi, A.K., Datta, S. (2010). Multi-Objective Optimization of Particle Reinforced Silicone Rubber Mould Material for Soft Tooling Process. 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_45

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  • DOI: https://doi.org/10.1007/978-3-642-17298-4_45

  • 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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