title: Hierarchical artificial bee colony algorithm for RFID network planning optimization.
abstract: This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP) problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.
authors.affiliation: Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office VII, Nanta Street No. 114, Dongling District, Shenyang 110016, China ; University of Chinese Academy of Sciences, Beijing 100039, China.
authors.forename: Lianbo
authors.initials: L
authors.lastname: Ma
authors.affiliation: Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office VII, Nanta Street No. 114, Dongling District, Shenyang 110016, China.
authors.forename: Hanning
authors.initials: H
authors.lastname: Chen
authors.affiliation: Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office VII, Nanta Street No. 114, Dongling District, Shenyang 110016, China.
authors.forename: Kunyuan
authors.initials: K
authors.lastname: Hu
authors.affiliation: Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Chinese Academy of Sciences, Faculty Office VII, Nanta Street No. 114, Dongling District, Shenyang 110016, China.
authors.forename: Yunlong
authors.initials: Y
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D000818:Animals; D001516:Bees / Q000502:physiology*; D008954:Models, Biological; D057233:Radio Frequency Identification Device / Q000379:methods*; D012919:Social Behavior