Hanning Chen

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In this paper, we develop an optimization model for planning the positions of readers in the RFID network based on a novel multi-swarm particle swarm optimizer called PSO. The main idea of PSO is to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology and enhanced dynamical update(More)
Bacterial Foraging Optimization (BFO) is a novel optimization algorithm based on the social foraging behavior of E. coli bacteria. However, the original BFO algorithm possesses a poor convergence behavior compared to the other successful nature-inspired algorithms. This paper presents a variation on the original BFO algorithm, namely the Cooperative(More)
and Applied Analysis 3 order to coordinate pattern emerges. In 18 , the proposed CBFO applied two cooperative approaches to the original BFO, namely, the serial heterogeneous cooperation on the implicit space decomposition level and the serial heterogeneous cooperation on the hybrid space decomposition level. In order to improve the BFO’s performance on(More)
Artificial Bee Colony ABC is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony CABC , which significantly improves the original ABC in solving complex optimization problems. Clustering is a popular data(More)
Article Bee Colony (ABC) is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents a variation on the original ABC algorithm, namely the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. In this work, CABC(More)
In order to obtain accurate and reliable network planning in the Radio Frequency Identification (RFID) communication system, the locations of readers and the associated values for each of the reader parameters have to be determined. All these choices must optimize a set of objectives, such as tag coverage, economic efficiency, load balance, and interference(More)
Bacterial foraging optimization (BFO) is a recently developed nature-inspired optimization algorithm, which is based on the foraging behavior of E. coli bacteria. However, BFO possesses a poor convergence behavior over complex optimization problems as compared to other nature-inspired optimization techniques like genetic algorithm (GA) and particle swarm(More)
In order to obtain accurate and reliable network planning in the RFID communications system, the locations of readers and the associated values for each of the reader parameters have to be determined. All these choice must optimize a set of objectives, such as coverage, economic efficiency, load balance and interference between readers. In this paper, we(More)
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(More)