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Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches
Joint Authors
Chen, Hanning
Niu, Ben
Ma, Lianbo
Zhu, Yunlong
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-01
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The development of radio frequency identification (RFID) technology generates the most challenging RFID network planning (RNP) problem, which needs to be solved in order to operate the large-scale RFID network in an optimal fashion.
RNP involves many objectives and constraints and has been proven to be a NP-hard multi-objective problem.
The application of evolutionary algorithm (EA) and swarm intelligence (SI) for solving multiobjective RNP (MORNP) has gained significant attention in the literature, but these algorithms always transform multiple objectives into a single objective by weighted coefficient approach.
In this paper, we use multiobjective EA and SI algorithms to find all the Pareto optimal solutions and to achieve the optimal planning solutions by simultaneously optimizing four conflicting objectives in MORNP, instead of transforming multiobjective functions into a single objective function.
The experiment presents an exhaustive comparison of three successful multiobjective EA and SI, namely, the recently developed multiobjective artificial bee colony algorithm (MOABC), the nondominated sorting genetic algorithm II (NSGA-II), and the multiobjective particle swarm optimization (MOPSO), on MORNP instances of different nature, namely, the two-objective and three-objective MORNP.
Simulation results show that MOABC proves to be more superior for planning RFID networks than NSGA-II and MOPSO in terms of optimization accuracy and computation robustness.
American Psychological Association (APA)
Chen, Hanning& Zhu, Yunlong& Ma, Lianbo& Niu, Ben. 2014. Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-511678
Modern Language Association (MLA)
Chen, Hanning…[et al.]. Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches. Mathematical Problems in Engineering No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-511678
American Medical Association (AMA)
Chen, Hanning& Zhu, Yunlong& Ma, Lianbo& Niu, Ben. Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-511678
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-511678