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Multi-objective Optimization of Methane Producing UASB Reactor Using a Combined Pareto Multi–objective Differential Evolution Algorithm (CPMDE)

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EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 288))

Abstract

Multi–objective optimization of an operating industrial wastewater treatment plant was carried out using combined Pareto multi–objective differential evolution (CPMDE) algorithm. The algorithm combines methods of Pareto ranking and Pareto dominance selections to implement a novel selection scheme at each generation. Modified methane generation and the Stover–Kincannon kinetic mathematical models were formulated for optimization. The conflicting objective functions that are optimized in this study include, maximization of volumetric methane production rate in the biogas produced at a lower hydraulic retention time and optimum temperature; minimization of effluent substrate concentration in order to meet the environmental discharge requirements based on the standard discharge limit, and finally, the minimization of biomass washout from the reactor. Wastewater flow rate, hydraulic retention time, efficiency of substrate utilization within the reactor, influent substrate concentration and operational temperature are the important decision variables related to this process. A set of non-dominated solutions with the high methane production rate at lower biomass and almost constant solution for the effluent concentration was obtained for the multi-objective optimization problem. In this study, the simulation results showed that the CPMDE approach can generate a better Pareto-front of the selected problem and its ability to solve unconstrained, constrained and real-world optimization problem was also demonstrated.

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Author information

Authors and Affiliations

  1. Department of Biotechnology and Food Technology, Durban University of Technology, Durban, South Africa

    Abimbola M. Enitan & Feroz M. Swalaha

  2. Institute for Water and Wastewater Technology, Department of Biotechnology, Durban University of Technology, Durban, South Africa

    Abimbola M. Enitan, Faizal Bux & Feroz M. Swalaha

  3. Department of Civil Engineering and Surveying, Durban University of Technology, P.O. Box 1334, Durban, 4000, South Africa

    Josiah Adeyemo & O. Oluwatosin Olofintoye

Authors
  1. Abimbola M. Enitan
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  2. Josiah Adeyemo
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  3. O. Oluwatosin Olofintoye
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  4. Faizal Bux
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  5. Feroz M. Swalaha
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Corresponding author

Correspondence to Abimbola M. Enitan .

Editor information

Editors and Affiliations

  1. Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg, Luxembourg

    Alexandru-Adrian Tantar

  2. Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg, Luxembourg

    Emilia Tantar

  3. School of Engineering, University of California, Merced, California, USA

    Jian-Qiao Sun

  4. College of Mechanical Engineering, Beijing University of Technology, Beijing, China

    Wei Zhang

  5. Department of Mechanics, Tianjin University, Tianjin, China

    Qian Ding

  6. Depto. Computación, CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze

  7. Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

    Michael Emmerich

  8. Université de Bordeaux, Bordeaux, France

    Pierrick Legrand

  9. School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales, Australia

    Pierre Del Moral

  10. Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico

    Carlos A. Coello Coello

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Enitan, A.M., Adeyemo, J., Olofintoye, O.O., Bux, F., Swalaha, F.M. (2014). Multi-objective Optimization of Methane Producing UASB Reactor Using a Combined Pareto Multi–objective Differential Evolution Algorithm (CPMDE). In: Tantar, AA., et al. EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V. Advances in Intelligent Systems and Computing, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-319-07494-8_22

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  • DOI: https://doi.org/10.1007/978-3-319-07494-8_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07493-1

  • Online ISBN: 978-3-319-07494-8

  • eBook Packages: EngineeringEngineering (R0)

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