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Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model
Jing, Shikai; Lian, Xiaodan; Chen HN(陈瀚宁); Zou T(邹涛); Ma LB(马连博)
作者部门工业控制网络与系统研究室
关键词Rfid Network Planning Hybrid Artificial Bee Colony Life-cycle Varying-population Distributed Decision Making
发表期刊Soft Computing
ISSN1432-7643
2017
卷号21期号:14页码:4055-4083
收录类别SCI ; EI
EI收录号20160902030922
WOS记录号WOS:000405500500019
产权排序3
资助机构National Natural Science Foundation of China under Grant Nos. 61503373, 61305028, 51205037, 61203161, and 51205389, and the Natural Science Foundation of Liaoning Province under Grant Nos. 2015020002, 201102200 and 201202226.
摘要Large-scale radio frequency identification (RFID) network planning (RNP) problem has been proven to be a NP-hard issue, which can be formulated as a high-dimensional nonlinear optimization problem with a mixture of discrete and continuous variables and uncertain parameters. First, a two-level optimization model for RFID network planning based on distributed decision making (DDM) is presented in this paper. In this model, the mixed discrete and continuous planning variables, namely the number, location, and radiate power of RFID readers are optimized. In each level of the optimization model, the different objectives to determine optimal values for these planning variables are as follows: (i) minimization of total installation cost of RFID network in the top-level; (ii) maximization of tag coverage and network reliability, and minimization of reader interference in the lower-level. In order to solve the proposed model effectively, this work proposes an efficient approach for RNP problem, namely the hybrid artificial bee colony optimizer (HABC), which employs the natural life-cycle mechanism to cast the original ABC framework to a cooperative and population varying fashion. In the proposed HABC, individuals can dynamically shift their survival states and population size varies dynamically according to the local fitness landscape during the executions of algorithm. These new characteristics of HABC help to avoid redundant search and maintain diversity of population in complex environments. Experiments are conducted on a set of CEC2005 and discrete benchmarks for evaluating the proposed algorithm. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.
语种英语
WOS标题词Science & Technology ; Technology
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
关键词[WOS]NUMERICAL FUNCTION OPTIMIZATION ; DIVISION-OF-LABOR ; PARTICLE SWARM ; ALGORITHM ; NETWORK ; CONSTRAINTS ; SEARCH
WOS研究方向Computer Science
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/17704
专题工业控制网络与系统研究室
通讯作者Chen HN(陈瀚宁); Zou T(邹涛); Ma LB(马连博)
作者单位1.School of Mechanical Engineering, Beijing Institute of Technology, Beijing, 110081, China
2.School of Computer Science and Software, Tianjin Polytechnic University, Tianjin, 300387, China
3.Laboratory of Information Service and Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
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GB/T 7714
Jing, Shikai,Lian, Xiaodan,Chen HN,et al. Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model[J]. Soft Computing,2017,21(14):4055-4083.
APA Jing, Shikai,Lian, Xiaodan,Chen HN,Zou T,&Ma LB.(2017).Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model.Soft Computing,21(14),4055-4083.
MLA Jing, Shikai,et al."Optimal layout and deployment for RFID system using a novel hybrid artificial bee colony optimizer based on bee life-cycle model".Soft Computing 21.14(2017):4055-4083.
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