Abstract The optimization of a complex system with multiple subsystems is a tough problem. In this paper, a Decentralized differential evolutionary algorithm (DDEA) is proposed. The simulations for both DDEA and centralized DE on three benchmark functions are carried out. The numerical results show that DDEA is efficient to solve decentralized optimization problems. On these problems, the proposed DDEA outperforms centralized DE in convergence.


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    Title :

    Decentralized Differential Evolutionary Algorithm for Large-Scale Networked Systems


    Contributors:
    Han, Guanghong (author) / Chen, Xi (author) / Zhao, Qianchuan (author)


    Publication date :

    2019-01-01


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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