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Hybrid Genetic Algorithm-Gravitational Search Algorithm to Optimize Multi-Scale Load Dispatch

Author

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  • D. Santra

    (RCC Institute of Information Technology, India)

  • A. Mukherjee

    (RCC Institute of Information Technology, India)

  • K. Sarker

    (Budge Budge Institute of Technology, India)

  • S. Mondal

    (Jadavpur University, India)

Abstract

Genetic algorithm (GA) and gravitational search algorithm (GSA) both have successfully been applied in solving ELD problems of electrical power generation systems. Each of these algorithms has their limitations and advantage. GA's global search and GSA's local search capability are their strong points while long execution period of GA and premature of convergence of GSA hinders the possibility of optimum result when applied separately in ELD problems. To mitigate these limitations, experiment is done for the first time by combining GA and GSA suitably and applying the hybrid in non-linear ELD problems of 6, 15, and 40 unit test systems. The paper reports the details of this study including comparative analysis considering similar hybrid algorithms. The result strongly attests the quality, consistency, and overall effectiveness of the GA-GSA hybrid in ELD problems.

Suggested Citation

  • D. Santra & A. Mukherjee & K. Sarker & S. Mondal, 2021. "Hybrid Genetic Algorithm-Gravitational Search Algorithm to Optimize Multi-Scale Load Dispatch," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 12(3), pages 28-53, July.
    • Handle: RePEc:igg:jamc00:v:12:y:2021:i:3:p:28-53
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    Cited by:

    1. Khairul Eahsun Fahim & Liyanage C. De Silva & Fayaz Hussain & Hayati Yassin, 2023. "A State-of-the-Art Review on Optimization Methods and Techniques for Economic Load Dispatch with Photovoltaic Systems: Progress, Challenges, and Recommendations," Sustainability, MDPI, vol. 15(15), pages 1-29, August.

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