多任务处理协同进化粒子群算法

doi:10.16451/j.cnki.issn1003-6059.201804004

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Abstract

The traditional particle swarm optimization(PSO) and its improved version aim to tackle the single task. With the development of electronic business, online severs need to deal with a batch of requests simultaneously, i.e. multitasking. Different from the parallel computer, the implicit parallelism of PSO is fully exploited, and co-evolution theory is introduced for multitasking. In the multitasking environment, different tasks correspond to different subpopulations, and the useful information is transferred from one subpopulation to another with a certain probability. Thus, co-evolutionary PSO for multitasking(CPSOM) is proposed in this paper. To verify the effectiveness of the proposed algorithm, CPSOM is used to solve a batch of function test problems, feature selection problems and constrained engineering optimization problems. Experimental results show that the useful information can be autonomously transferred from one task to another in the CPSOM environment. Moreover, cooperation of different tasks enhance the solution quality and speed up the convergence.

Key words： Multitasking Particle Swarm Optimization(PSO) Co-evolution Function Optimization Attribute Selection Engineering Application

Received: 21 August 2017

ZTFLH:

TP 18

Fund:

Supported by Major Program of National Natural Science Foundation of China(No.71490725), Training Program of Major Research Plan of National Natural Science Foundation of China(No.91546108)

Corresponding Authors: CHENG Meiying(Corresponding author), Ph.D., lecturer. Her research interests include swarm intelligent algorithm and data mining.

About author:: QIAN Qian, master, lecturer. His research interests include evolutionary computation;NI Zhiwei, Ph.D., professor. His research interests include data mining, machine lear-ning and artificial intelligence;ZHU Xuhui, Ph.D. candidate. His research interest include intelligent computation and machine learning.

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Cite this article:

CHENG Meiying,QIAN Qian,NI Zhiwei等. Co-evolutionary Particle Swarm Optimization for Multitasking[J]. , 2018, 31(4): 322-334.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201804004 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I4/322

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