Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9 September 2021, Sakarya, Turkey

Research Article

A New Version of Modified Camel Algorithm for Engineering Applications

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  • @INPROCEEDINGS{10.4108/eai.7-9-2021.2314874,
        author={Ramzy S. Ali and Jawad R. Mahmood and Hussein M. Badr},
        title={A New Version of Modified Camel Algorithm for Engineering Applications},
        proceedings={Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9 September 2021, Sakarya, Turkey},
        publisher={EAI},
        proceedings_a={IMDC-IST},
        year={2022},
        month={1},
        keywords={new modified camel algorithm; distributed generation; solar photovoltaic; congestion problem; power loss; voltage profile},
        doi={10.4108/eai.7-9-2021.2314874}
    }
    
  • Ramzy S. Ali
    Jawad R. Mahmood
    Hussein M. Badr
    Year: 2022
    A New Version of Modified Camel Algorithm for Engineering Applications
    IMDC-IST
    EAI
    DOI: 10.4108/eai.7-9-2021.2314874
Ramzy S. Ali1,*, Jawad R. Mahmood1, Hussein M. Badr2
  • 1: Electrical Engineering Department, College of Engineering, University of Basrah, Iraq
  • 2: Training and Energy Research Office, Ministry of Electricity, Iraq, Baghdad
*Contact email: ramzy.ali@uobasrah.edu.iq

Abstract

The paper presents the new modified camel algorithm (NMCA) as a new optimization method for solving optimization tasks. NMCA is different from the modified camel algorithm (MCA) and other metaheuristic algorithms. Where it provides a new insight for global optimization. The proposed method is verified using power distribution system problems (engineering problems) commonly used in the area of optimization. Simulations were conducted on the IEEE 69- and 33-bus systems. The NMCA algorithm successfully achieved the optimal solutions at various test cases. NMCA results are further compared with MCA and well-known optimization algorithms. The results show that the NMCA is efficiently capable of solving optimization problems.