Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 8
2376-2380

Local parallel search framework for distributed constraint optimization problems

Shi Meifeng
Yang Hai
Chen Yuan
Xiao Shichuan
Liao Xin
He Ying
College of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China
DOI: 10.19734/j.issn.1001-3695.2022.02.0035

Abstract

In order to solve the problem that it is difficult to get out of the local optimum to achieve further optimization in large-scale dense distributed constraint optimization problems(DCOP), this paper proposed a local parallel search framework(LPOS) for solving algorithms of DCOP. In LPOS, the agent searched all the value assignments of its local neighbors in parallel according to its current value assignment to further expand the search of solution space, so as to avoid the algorithm falling into local optimum prematurely. In order to ensure the convergence of the algorithm, this paper designed an adaptive equilibrium factor K to balance the exploration and exploitation ability of the DCOP solving algorithms. At the theoretical analysis, it proved that the LPOS could expand the search of solution space and the K could achieve the balance. The experimental results demonstrate that the performance of the proposed LPOS is better than the-state-of-the-art algorithms in both low density and high density. Specifically, LPOS significantly superior to the competitors when solving high density DCOP.

Foundation Support

重庆市教育委员会科学技术研究计划青年项目资助项目(KJQN202001139)
重庆市基础研究与前沿探索项目(cstc2018jcyjAX0287)
重庆理工大学科研启动基金资助项目(2019ZD03)
重庆理工大学研究生创新项目(clgycx20202094)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.02.0035
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 8
Section: Algorithm Research & Explore
Pages: 2376-2380
Serial Number: 1001-3695(2022)08-023-2376-05

Publish History

[2022-03-31] Accepted Paper
[2022-08-05] Printed Article

Cite This Article

石美凤, 杨海, 陈媛, 等. 基于局部并行搜索的分布式约束优化算法框架 [J]. 计算机应用研究, 2022, 39 (8): 2376-2380. (Shi Meifeng, Yang Hai, Chen Yuan, et al. Local parallel search framework for distributed constraint optimization problems [J]. Application Research of Computers, 2022, 39 (8): 2376-2380. )

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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