By Topic

Optimal RFID networks planning using a hybrid evolutionary algorithm and swarm intelligence with multi-community population structure

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Han Feng ; College of Information Science and Technology, Donghua University, Shanghai, China ; Jie Qi

The problem of choosing the optimum locations and the associated parameters of readers in RFID communication systems is considered. All these choices must satisfy a set of objectives, such as tag coverage, load balance, economic efficiency, and interference in order to obtain accurate and reliable network planning. In this paper, a novel optimization algorithm, namely the multi-community GA-PSO, is proposed to solve the complicated RFID network planning problem of large-scale system. The main idea of the algorithm is to divide the single population of the canonical PSO into multi-swarm and use the genetic selection and mutation strategy to improve particle swarm dynamic rules. The simulation results show that the proposed algorithm obtains the superior solution for networking planning problem than canonical PSO does.

Published in:

Advanced Communication Technology (ICACT), 2012 14th International Conference on

Date of Conference:

19-22 Feb. 2012