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A dual-population search differential evolution algorithm for functional distributed constraint optimization problems

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Abstract

Functional Distributed Constraint Optimization Problems (F-DCOPs) is a constraint processing framework for continuous variables in multi-agent system modeling. In the past years, researchers have proposed many F-DCOP solving algorithms with excellent performance. Nonetheless, there are some shortcomings in existing F-DCOP solving algorithms, such as the lack of anytime property, the limitation of constraint cost functions, and the inability to guarantee convergence. To deal with these problems, we proposed a Dual-population Search Differential Evolution Algorithm for F-DCOP (DSDE-FD). Firstly, we designed dual-population for local and global search respectively to balance the exploration and exploitation. Secondly, specific mutation operators are designed for local and global population. Finally, adaptive population size is designed to balance computational overhead and search ability. It is proved that the proposed algorithm is an anytime algorithm and has global convergence.The extensive experiments performed based on four types of benchmark problems shown that the proposed algorithm outperforms state-of-the-art F-DCOP solving algorithms.

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Acknowledgments

This work is supported by Youth Project of Science and Technology Research Program of Chongqing Education Commission of China (No. KJQN202001139), Chongqing Research Program of Basic Research and Frontier Technology(NO. cstc2018jcyjAX0287), Postgraduate Innovation Project of Chongqing University of Technology (NO. clgycx 20203110) and Scientific Research Foundation of Chongqing University of Technology (NO. 2019ZD03).

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Authors and Affiliations

  1. College of Computer Science and Engineering, Chongqing University of Technology, Hongguang Avenue, Banan Distric, 401320, Chongqing, China

    Meifeng Shi, Xin Liao & Yuan Chen

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  1. Meifeng Shi
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  2. Xin Liao
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  3. Yuan Chen
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Correspondence to Xin Liao.

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Shi, M., Liao, X. & Chen, Y. A dual-population search differential evolution algorithm for functional distributed constraint optimization problems. Ann Math Artif Intell 90, 1055–1078 (2022). https://doi.org/10.1007/s10472-022-09805-2

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