[1]Cheng Shi,Wang Rui,Wu Guohua,et al.Swarm intelligence optimization algorithm[J].Journal of Zhengzhou University (Engineering Science),2018,39(06):1-2.[doi:10.13705/j.issn.1671-6833.2018.06.024]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
39
Number of periods:
2018 06
Page number:
1-2
Column:
Public date:
2018-10-24
- Title:
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Swarm intelligence optimization algorithm
- Author(s):
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Cheng Shi 1; Wang Rui 2; Wu Guohua 3; Guo Yinan 4; Malembo 5; Shi Yuhui 6
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1. School of Computer Science, Shaanxi Normal University; 2. School of Systems Engineering, National University of Defense Technology; 3. School of Transportation Engineering, Central South University; 4. School of Information and Control Engineering, China University of Mining and Technology; 5. School of Software, Northeastern University; 6. Department of Computer Science and Engineering, Southern University of Science and Technology
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- Keywords:
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Swarm intelligence; optimization algorithms; intelligent computing
- CLC:
-
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- DOI:
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10.13705/j.issn.1671-6833.2018.06.024
- Abstract:
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The core idea of swarmintelligence (swarmintelligence) is that several simple individuals form a group, through cooperation, competition, interaction and learning mechanisms to show advanced and complex functions, in the absence of local information and models, still able to complete the solution of complex problems.The solution process is to initialize the variable randomly, and calculate the output value of the objective function after iterative solution.Swarm intelligent optimization algorithm is not dependent on gradient information, and it is not continuous and derivable to solve problems, which makes it suitable for both continuous numerical optimization and discrete combinational optimization.At the same time, the potential parallelism and distributed characteristics of swarm intelligence optimization algorithm make it have significant advantages in dealing with big data.