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A radio frequency identification network design methodology for the decision problem in Mackay Memorial Hospital based on swarm optimization
Conference paper

A radio frequency identification network design methodology for the decision problem in Mackay Memorial Hospital based on swarm optimization

Wei-Chang Yeh, Yuan-Ming Yeh, Chun-Hua Chou, Y.-Y. Chung and Xiangjian He
2012 IEEE Congress on Evolutionary Computation, CEC 2012, 6256641
2012
Appears in  keyword about Art

Abstract

binary search fuzzy adaptive resonance theory (fuzzy-ART) k-means network design Radio-frequency identification (RFID) simplified swarm optimization (SSO) soft computing
Radio-frequency identification (RFID) is an automatic identification system which has become a hot topic in the fields of manufacturing, logistics, and so on. The purpose of this research is to propose a methodology for designing the RFID network planning problem (RNP) for application in the Mackay Memorial Hospital in Hsinchu, Taiwan. In this study, the RFID network is first considered as a grid and divided into several small squares. A soft computing methodology called FKB-SSO is proposed to solve the RNP problem based on simplified swarm optimization (SSO) by integrating k-means, fuzzy adaptive resonance theory (fuzzy-ART), and binary search. The proposed FKB-SSO will provide the basis for strategic decisions in constructing the RFID network to reduce the number of RFID readers with a minimal budget under the constraint of 100% coverage rate. The proposed FKB-SSO is more efficient than PSO and experts' manual solution in both run time and solution quality. © 2012 IEEE.

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