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Applications of Genetic Algorithms in Chemical Engineering I: Methodology

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Applications of Metaheuristics in Process Engineering

Abstract

The fascinating world of genes has been an inspiration for mankind. One such inspiration has led to a popular optimization technique, genetic algorithm (GA). Its inherent parallelism has enabled significant computational improvement over deterministic enumerations. Further, it has provided a flexibility of solving multiple objectives in a derivative-free environment. These advantages are extremely useful for solving optimization problems in chemical engineering, ranging over a wide variety of processes from the production of bulk chemicals to highly sophisticated specialty chemicals, their purification, control, planning, and scheduling. These systems are often associated with multiple objectives and complex model equations. Several variations of GA have been developed over the last four decades by incorporating ground-breaking concepts such as elitism, jumping gene, crowding distance, ranking, altruism, etc., to enable faster convergence of the algorithms. Continuous improvements are being made by the use of new or hybrid concepts so as to provide improved applicability and flexibility, and so as to exploit the rapidly increasing computational speeds.

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Authors and Affiliations

  1. Department of Chemical Engineering, University of Petroleum and Energy Studies (UPES), Bidholi, via Prem Nagar, Dehradun, Uttarakhand, 248007, India

    Santosh K. Gupta

  2. Department of Chemical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, 110016, India

    Manojkumar Ramteke

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  1. Santosh K. Gupta
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  2. Manojkumar Ramteke
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Correspondence to Santosh K. Gupta .

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Editors and Affiliations

  1. Evol. Comput. & Image Proc. Group, Center for Develop. of Adv. Computing, Pune, India

    Jayaraman Valadi

  2. Lab. LiSSi (EA 3956), Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

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Gupta, S.K., Ramteke, M. (2014). Applications of Genetic Algorithms in Chemical Engineering I: Methodology. In: Valadi, J., Siarry, P. (eds) Applications of Metaheuristics in Process Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-06508-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-06508-3_2

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