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Proceedings ArticleDOI

Genetic Approach for Network Planning in the RFID Systems

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TLDR
A genetic approach for tackling the complex optimization problem of choosing the optimum locations for readers (antennas) in a RFID communications system is presented and computational results are presented for a typical test scenario.
Abstract
The problem of choosing the optimum locations for readers (antennas) in a RFID communications system is considered. All these choices must satisfy a set of imperative constraints and optimize a set of objectives. The factors affecting optimum selection are the complex propagation environments, the undesired mutual coverage and the unavoidable interference of multiple readers. Unlike the antenna positioning in traditional cellular networks, uplink signals, i.e. signals from tag towards reader, must be taken into account when dealing with the planning in the RFID networks. This paper presents a genetic approach for tackling this complex optimization problem. To validate this approach, computational results are presented for a typical test scenario.

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Citations
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Journal ArticleDOI

An RFID network design methodology for asset tracking in healthcare

TL;DR: The purpose of this research is to provide decision makers with a methodology to optimize the design of a medical-asset tracking system constrained by a limited number of RFID readers.
Journal ArticleDOI

Optimizing RFID Network Planning by Using a Particle Swarm Optimization Algorithm With Redundant Reader Elimination

TL;DR: A novel particle swarm optimization (PSO) algorithm with a tentative reader elimination (TRE) operator to deal with RNP and results show that the proposed algorithm is capable of achieving higher coverage and using fewer readers than the other algorithms.
Journal ArticleDOI

Original research paper: Multi-colony bacteria foraging optimization with cell-to-cell communication for RFID network planning

TL;DR: The main idea of MC-BFO is to extend the single population bacterial foraging algorithm to the interacting multi-colony model by relating the chemotactic behavior of single bacterial cell to the cell-to-cell communication of bacterial community.
Journal ArticleDOI

Cooperative artificial bee colony algorithm for multi-objective RFID network planning

TL;DR: Simulation results show that CMOABC proves to be superior for planning RFID networks compared to NSGA-II and MOABC in terms of optimization accuracy and computation robustness.
Journal ArticleDOI

RFID network planning using a multi-swarm optimizer

TL;DR: An optimization model for planning the positions of readers in the RFID network based on a novel Multi-swarm Particle Swarm Optimizer called PS2O, which is to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology and enhanced dynamical update equations.
References
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Book

Genetic algorithms in search, optimization, and machine learning

TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Book

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TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
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TL;DR: A critical review of the most important evolutionary-based multiobjective optimization techniques developed over the years, emphasizing the importance of analyzing their Operations Research roots as a way to motivate the development of new approaches that exploit the search capabilities of evolutionary algorithms.
Book

RFID Handbook: Radio-Frequency Identification Fundamentals and Applications

TL;DR: Differentiation of RFID systems fundamentals ofRFID systems physical basics frequency ranges and regulations coding and modulation data integrity cryptography standards architecture of electronic carriers readers production of transponders and contactless smart cards applications of RF ID systems market guide.
Journal ArticleDOI

Planning effective cellular mobile radio networks

TL;DR: An optimization framework based on simulated annealing is used for site selection and for base-station configuration and shows that cellular network design problems are tractable for realistic problem instances.
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