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Algorithm Research & Explore
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2683-2688

Random disturbance based multi-population ant colony algorithm to solve distributed constraint optimization problems

Shi Meifeng
Xiao Shichuan
Feng Xin
College of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China

Abstract

Ant colony algorithms to solve distributed constraint optimization problems(ACO_DCOP) have some shortcomings including very slow convergence speed and easily falling into local optima. To cope with these issues, this paper proposed a RDMAD. The method introduced a division of labor and cooperation mechanism to divide the population into two subpopulations for greedy search and heuristic search respectively. It also constructed a hierarchical update strategy to speed up convergence and improve solution quality. Furthermore, this paper designed an adaptive mutation operator and a reward and punishment mechanism for the greedy search subpopulation to prevent RDMAD falling into the local optima. Simultaneously, this paper introduced a random disturbance strategy to increase the population diversity when RDMAD was stagnant. To verify the performance of the proposed algorithm, it compared RDMAD with the other seven advanced incomplete algorithms on three types of benchmark problems. The extensive experimental results show that the RDMAD algorithm is significantly superior to the state-of-the-arts algorithms in solution quality and convergence speed. In addition, RAMAD is far stable than the competing algorithms.

Foundation Support

重庆市教育委员会科学技术研究计划青年资助项目(KJQN202001139)
重庆市基础研究与前沿探索资助项目(cstc2018jcyjAX0287)
重庆理工大学研究生创新项目(clgycx20203116)
重庆理工大学科研启动基金资助项目(2019ZD03)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.03.0084
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Algorithm Research & Explore
Pages: 2683-2688
Serial Number: 1001-3695(2022)09-019-2683-06

Publish History

[2022-05-11] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

石美凤, 肖诗川, 冯欣. 基于多种群的随机扰动蚁群算法求解分布式约束优化问题 [J]. 计算机应用研究, 2022, 39 (9): 2683-2688. (Shi Meifeng, Xiao Shichuan, Feng Xin. Random disturbance based multi-population ant colony algorithm to solve distributed constraint optimization problems [J]. Application Research of Computers, 2022, 39 (9): 2683-2688. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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