Abstract
The Radio Frequency Identification system (RFID) is a generic term for technologies of a type of automatic identification system that use radio-frequency waves to automatically identify people or objects. Multiple RFID readers are required to detect and monitor the tags in the network area due to their limited interrogation range. Therefore, the cost of the RFID System, its efficiency in the communication process, and the number of tags covered directly depend on the number of deployed readers. In this work, we present a new many/multi-objective model with the aim to achieve the optimal solutions of the NP-hard problem of RFID Network Planning (RNP). The model involves many objectives and constraints as determining the minimum number of readers, finding their optimal 3D deployment and localization, guarantying a full coverage of all the tags distributed in the area, and minimizing the energy and the interferences caused by an overlap in the readers signals and the tags responds at the same time. Moreover, we provide a new decision aid application with the aim to access, manage, solve, and optimize the RNP problem involving the needs of researchers and decision makers.
Highlights
The term RFID refers to the Radio Frequency Identification system, which is an automated data collection technology that use radio-frequency waves to automatically identify and track objects
In order to achieve the optimal deployment of the RFID Network Planning problem (RNP) [2, 3], it’s becoming difficult to ignore the number of objectives to satisfy as determining the minimum number of deployed readers, guarantying a full coverage of all the tags distributed in the area, and minimizing the energy and the interferences caused by an overlap in the readers signals and the tags responds at the same time
There is a large volume of published studies describing the role of the RFID Network Planning (RNP) and presenting several keys in order to achieve the optimal deployment of RFID readers
Summary
The term RFID refers to the Radio Frequency Identification system, which is an automated data collection technology that use radio-frequency waves to automatically identify and track objects. In order to achieve the optimal deployment of the RFID Network Planning problem (RNP) [2, 3], it’s becoming difficult to ignore the number of objectives to satisfy as determining the minimum number of deployed readers, guarantying a full coverage of all the tags distributed in the area, and minimizing the energy and the interferences caused by an overlap in the readers signals and the tags responds at the same time. Several attempts have been made to achieve the optimal RFID network planning, mostly by using the multi-objective optimization [4] based on operators and algorithms. There is a large volume of published studies describing the role of the RFID Network Planning (RNP) and presenting several keys in order to achieve the optimal deployment of RFID readers. We deal with the needs of the decision maker by providing a full decision aid platform with the aim to access, manage, solve, and optimize the RNP problem for academic and real-world applications of the RFID system
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