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Fireflies in the Fruits and Vegetables: Combining the Firefly Algorithm with Goal Programming for Setting Optimal Osmotic Dehydration Parameters of Produce

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Recent Advances in Swarm Intelligence and Evolutionary Computation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 585))

Abstract

This study employs the Firefly Algorithm (FA) to determine the optimal parameter settings needed in the osmotic dehydration process of fruits and vegetables. Two case studies are considered. For both cases, the functional form of the osmotic dehydration model is established using response surface techniques with the resulting optimization formulations being non-linear goal programming models. For optimization purposes, a computationally efficient, FA-driven method is employed and the resulting solutions are shown to be superior to those from previous approaches for the osmotic process parameters. The final component of this study provides a computational experimentation performed on the FA to illustrate the relative sensitivity of this nature-inspired metaheuristic approach over a range of the two key parameters that most influence its running time.

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Authors and Affiliations

  1. Technology and Operations Management, Harvard Business School, Boston, MA, 02163, USA

    Raha Imanirad

  2. OMIS Area, Schulich School of Business, York University, Toronto, ON, M3J 1P3, Canada

    Julian Scott Yeomans

Authors
  1. Raha Imanirad
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  2. Julian Scott Yeomans
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Correspondence to Julian Scott Yeomans .

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Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

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Imanirad, R., Yeomans, J.S. (2015). Fireflies in the Fruits and Vegetables: Combining the Firefly Algorithm with Goal Programming for Setting Optimal Osmotic Dehydration Parameters of Produce. In: Yang, XS. (eds) Recent Advances in Swarm Intelligence and Evolutionary Computation. Studies in Computational Intelligence, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-13826-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-13826-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13825-1

  • Online ISBN: 978-3-319-13826-8

  • eBook Packages: EngineeringEngineering (R0)

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