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Comparative Study of Multi/Many-Objective Evolutionary Algorithms on Hot Rolling Application

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Optimization in Industry

Part of the book series: Management and Industrial Engineering ((MINEN))

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Abstract

Handling multiple number of objectives in industrial optimization problems is a regular affair. The journey of development of evolutionary algorithms for handling such problems occurred in two phases. In the first phase, multi-objective optimization algorithms are developed that worked quite satisfactorily while finding Pareto set of solutions for two to three objectives. However, their success rates for finding the Pareto optimal solutions for higher number of objectives were limited which triggered the development of different sets of evolutionary algorithms under the name of many-objective optimization algorithms. In this work, we intend to compare the performance of these two classes of algorithms for an industrial hot rolling operation from a real-life steel plant. Several process, chemistry and geometry related parameters are modelled to yield different mechanical properties such as % elongation , ultimate tensile strength and yield strength of final hot rolled steel product through data-based techniques such as artificial neural networks (ANN) . Using this ANN model, the mechanical properties are maximized to obtain the Pareto trade-off solutions using both non-dominated sorting genetic algorithms II (NSGA-II) and many-objective evolutionary algorithm decomposition and dominance (MOEA/DD) and their solutions are compared using a suitable metric for identifying the extent of convergence and diversity. This kind of Pareto set provides a designer with ample of alternatives before choosing a solution for final implementation.

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Authors and Affiliations

  1. Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, 502285, Telangana, India

    Prateek Mittal, Affan Malik & Kishalay Mitra

  2. Research & Development, Tata Steel Limited, Jamshedpur, 831001, Jharkhand, India

    Itishree Mohanty

Authors
  1. Prateek Mittal
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  2. Affan Malik
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  3. Itishree Mohanty
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  4. Kishalay Mitra
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Correspondence to Kishalay Mitra .

Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, SRM Institute of Science and Technology, Chennai, India

    Shubhabrata Datta

  2. Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal

    J. Paulo Davim

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Mittal, P., Malik, A., Mohanty, I., Mitra, K. (2019). Comparative Study of Multi/Many-Objective Evolutionary Algorithms on Hot Rolling Application. In: Datta, S., Davim, J. (eds) Optimization in Industry. Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-01641-8_12

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  • DOI: https://doi.org/10.1007/978-3-030-01641-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01640-1

  • Online ISBN: 978-3-030-01641-8

  • eBook Packages: EngineeringEngineering (R0)

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