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Availability and performance optimization of physical processing unit in sewage treatment plant using genetic algorithm and particle swarm optimization

Author

Listed:
  • Deepak Sinwar

    (Manipal University Jaipur)

  • Monika Saini

    (Manipal University Jaipur)

  • Dilbag Singh

    (Manipal University Jaipur)

  • Drishty Goyal

    (Manipal University Jaipur)

  • Ashish Kumar

    (Manipal University Jaipur)

Abstract

Predicting the optimum availability of the physical processing unit of sewage treatment plant is defined as a Nondeterministic Polynomial time-hard problem. Recently many researchers have utilized soft computing techniques to handle this issue. However, the existing techniques are far from the optimal solutions as soft computing techniques suffer from various issues such as, poor computational speed, getting stuck in local optima, pre-mature convergence, etc. Therefore, in this work a novel mathematical model is designed and implemented using Markov process and Chapman-Kolmogorov equations derived by assuming arbitrary repair rates and exponentially distributed failure rates. Thereafter, Genetic Algorithm and Particle Swarm Optimization techniques are utilized to optimize the availability and performance of physical processing unit. The needed data has been collected with the help of plant personnel and results are also shared with them. Experimental results reveal that the Particle Swarm Optimization based proposed model outperforms the competitive techniques.

Suggested Citation

  • Deepak Sinwar & Monika Saini & Dilbag Singh & Drishty Goyal & Ashish Kumar, 2021. "Availability and performance optimization of physical processing unit in sewage treatment plant using genetic algorithm and particle swarm optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1235-1246, December.
    • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:6:d:10.1007_s13198-021-01163-2
    DOI: 10.1007/s13198-021-01163-2
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    References listed on IDEAS

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    1. Amit Kumar & Vinod Kumar & Vikas Modgil, 2018. "Performance optimisation for ethanol manufacturing system of distillery plant using particle swarm optimisation algorithm," International Journal of Intelligent Enterprise, Inderscience Enterprises Ltd, vol. 5(4), pages 345-364.
    2. V. N. Aju kumar & Piyush Gupta & O. P. Gandhi, 2019. "Maintenance performance evaluation using an integrated approach of graph theory, ISM and matrix method," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(1), pages 57-82, February.
    3. Shashank Gupta & Piyush Gupta & Aditya Parida, 2017. "Modeling lean maintenance metric using incidence matrix approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(4), pages 799-816, December.
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    Cited by:

    1. Mousumi Banerjee & Vanita Garg & Kusum Deep, 2023. "Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine cosine algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 307-327, March.

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