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Design Optimization of Plate-Fin Heat Exchanger by Using Modified Jaya Algorithm

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Advanced Engineering Optimization Through Intelligent Techniques

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 949))

Abstract

In the present paper, bi-objective optimization of plate-fin heat exchanger (PFHE) is considered. An advanced optimization algorithms called TLBO, Jaya algorithm (JA), and its modified version known as self-adaptive Jaya algorithms are applied for the design and optimization of PFHE. The minimization of cost and volume of PFHE is selected as an objective function and optimized both objective functions simultaneously. The outcomes achieved by TLBO, JA, and modified JA for considered optimization problems are found superior as compared to particle swarm optimization (PSO) and genetic algorithm (GA). In case of function evaluations, computational time and population size demanded by the modified JA are lesser than various algorithms. In case of combined objective function, the results found by TLBO, JA, and modified JA are 11.84% better in volume and 12.41% better in the total cost as associated with the outcomes using GA.

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Authors and Affiliations

  1. Department of Mechanical Engineering, DYPatil Institute of Engineering and Technology, 410506, Pune, India

    Kiran Chunilal More

  2. Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, 395007, Surat, India

    R. Venkata Rao

Authors
  1. Kiran Chunilal More
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  2. R. Venkata Rao
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Corresponding author

Correspondence to Kiran Chunilal More .

Editor information

Editors and Affiliations

  1. Sardar Vallabhbhai National Institute of Technology, Surat, Surat, Gujarat, India

    R. Venkata Rao

  2. Cracow University of Technology, Kraków, Poland

    Jan Taler

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More, K.C., Venkata Rao, R. (2020). Design Optimization of Plate-Fin Heat Exchanger by Using Modified Jaya Algorithm. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_15

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