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

Mittal, Prateek and Malik, Affan and Mohanty, Itishree and Mitra, Kishalay (2018) Comparative Study of Multi/Many-Objective Evolutionary Algorithms on Hot Rolling Application. In: Optimization in Industry. Management and Industrial Engineering . Springer, pp. 331-349. ISBN 9783030016401

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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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IITH Creators:
IITH CreatorsORCiD
Mitra, Kishalay
Item Type: Book Section
Uncontrolled Keywords: Many-objective optimization, NSGA-II, MOEA-DD, Hot rolling, Chemistry parameter, Geometry parameter, Elongation, Ultimate tensile strength, Yield strength, ANN, IGD
Subjects: Chemical Engineering
Divisions: Department of Chemical Engineering
Depositing User: Team Library
Date Deposited: 28 Nov 2018 08:55
Last Modified: 28 Nov 2018 08:55
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