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A non-convex economic load dispatch problem using chameleon swarm algorithm with roulette wheel and Levy flight methods

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Abstract

An Enhanced Chameleon Swarm Algorithm (ECSA) by integrating roulette wheel selection and Lé vy flight methods is presented to solve non-convex Economic Load Dispatch (ELD) problems. CSA has diverse strategies to move towards the optimal solution. Even so, this algorithm’s performance faces some hurdles, such as early convergence and slumping into local optimum. In this paper, several enhancements were made to this algorithm. First, it’s position updating process was slightly tweaked and took advantage of the chameleons’ randomization as well as adopting several time-varying functions. Second, the Lévy flight operator is integrated with roulette wheel selection method and both are combined with ECSA to augment the exploration behavior and lessen its bias towards exploitation. Finally, an add-on position updating strategy is proposed to develop a further balance between exploration and exploitation conducts. The optimization performance of ECSA is shown by testing it on five various real ELD cases with a generator having 3, 13, 40, 80 and 140 units, each with different constraints. The results of the ELD systems’ analysis depict that ECSA is better than the parent CSA and other state-of-the art methods. Further, the efficacy of ECSA was experimented on several benchmark test functions, and its performance was compared to other well-known optimization methods. Experimental results show that ECSA surpasses other methods on complex benchmark functions with modest computational burdens. The superiority and practicality of ECSA is demonstrated by getting new best solutions for large-scale ELD cases such as 40-unit and 140-unit test systems.

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Acknowledgements

This work is supported by the Deanship of Scientific Research & Innovation at the Al-Zaytoonah University of Jordan granted to the second author (Grant No. 2022-2021/08/17).

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Authors and Affiliations

  1. Department of Computer Science, Al-Balqa Applied University, Salt, Jordan

    Malik Sh. Braik & Abdelaziz I. Hammouri

  2. Department of Computer Science, Al-Aqsa University, P.O. Box 4051, Gaza, Palestine

    Mohammed A. Awadallah

  3. Artificial Intelligence Research Center (AIRC), Ajman University, Ajman, United Arab Emirates

    Mohammed A. Awadallah

  4. Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan

    Mohammed A. Awadallah

  5. Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, United Arab Emirates

    Mohammed Azmi Al-Betar

  6. Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, Al-Salt, Jordan

    Mohammed Azmi Al-Betar

  7. Sorbonne Center of Artificial Intelligence, Sorbonne University, Abu Dhabi, UAE

    Raed Abu Zitar

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  1. Malik Sh. Braik
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Appendix A: CEC-2015 Test Functions

Appendix A: CEC-2015 Test Functions

Detailed descriptions of the CEC-2015 benchmark functions are tabulated in Table 31.

Table 31 A description of the CEC-2015 benchmark test functions
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Braik, M.S., Awadallah, M.A., Al-Betar, M.A. et al. A non-convex economic load dispatch problem using chameleon swarm algorithm with roulette wheel and Levy flight methods. Appl Intell 53, 17508–17547 (2023). https://doi.org/10.1007/s10489-022-04363-w

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