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Black Hole—White Hole Algorithm for Dynamic Optimization of Chemically Reacting Systems

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Congress on Intelligent Systems (CIS 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1335))

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Abstract

Black hole (BH) meta-heuristic optimization is a nature-inspired algorithm which mimics the behavior of black holes. The Black hole algorithm framework is implemented in this work to solve dynamic optimization of some benchmark problems encountered in chemically reacting systems. We have employed two different algorithm types which include a standalone black hole algorithm and an algorithm which combines exploration–exploitation tradeoff in the algorithm. This tradeoff is enabled through the concept of white hole (WH). We have employed both piecewise linear and piecewise constant control profiles in our simulations. The algorithms proposed are simple and are easy to implement. Case studies studied show that the novel algorithms are robust and compare very well with existing algorithms.

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Author information

Authors and Affiliations

  1. Flame University, Pune, 412115, India

    Jayaraman K. Valadi

  2. Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune, 411007, India

    Prasad Ovhal

Authors
  1. Prasad Ovhal
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  2. Jayaraman K. Valadi
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, Rajasthan, India

    Harish Sharma

  2. Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

    Mukesh Saraswat

  3. National Institute of Technology, Jalandhar, Punjab, India

    Anupam Yadav

  4. Korea University, Seoul, Korea (Republic of)

    Joong Hoon Kim

  5. South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

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Ovhal, P., Valadi, J.K. (2021). Black Hole—White Hole Algorithm for Dynamic Optimization of Chemically Reacting Systems. In: Sharma, H., Saraswat, M., Yadav, A., Kim, J.H., Bansal, J.C. (eds) Congress on Intelligent Systems. CIS 2020. Advances in Intelligent Systems and Computing, vol 1335. Springer, Singapore. https://doi.org/10.1007/978-981-33-6984-9_43

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