Plenary Lecture

Swarm Intelligence Metaheuristics Applied to the Multi-Objective RFID Network Planning Problem

Professor Milan Tuba
Faculty of Computer Science
John Naisbitt University

Abstract: Radio frequency identification (RFID) systems consist of tags, usually cheap and passive, without power supply, and more expensive and powered readers. Tags and readers communicate with each other by radio waves through antennas. Tags are attached to the items that are subject of tracking (items in stores or storages, clothes, cars, animals, etc.) and they respond by backscattering portion of the received reader’s signal. Radio frequency identification (RFID) technology is very important today and its usage is significantly increasing in many fields such as logistics, production, supply chain management, asset tracking, etc. RFID network planning problem is a multi-objective hard optimization problem which deals with optimal deployment of sufficient number of readers with the goals of establishing a sufficient coverage of the tags, reducing power consumption, reducing interference between readers, etc. Optimization is done by adjusting the control variables (readers’ coordinates, the number of readers, antenna parameters, etc.) of the system. Swarm intelligence algorithms, as a successful branch of nature inspired metaheuristics, have been successfully used to tackle such hard optimization problems. Different swarm intelligence algorithms (mostly PSO) have been used to solve multi-objective RFID network planning problem. Also, different approaches were used to handle multiple objectives where weighted coefficients transformation of the multi-objective problem to a single-objective one was most common. In this plenary lecture few successful swarm intelligence algorithms applications to the multi-objective RFID network planning problem will be presented.

Brief Biography of the Speaker: Milan Tuba is the Dean of Graduate School of Computer Science and Provost for mathematical and technical sciences at John Naisbitt University of Belgrade. He received B. S. in Mathematics, M. S. in Mathematics, M. S. in Computer Science, M. Ph. in Computer Science, Ph. D. in Computer Science from University of Belgrade and New York University. From 1983 to 1994 he was in the U.S.A. first as a graduate student and teaching and research assistant at Vanderbilt University in Nashville and Courant Institute of Mathematical Sciences, New York University and later as Assistant Professor of Electrical Engineering at Cooper Union School of Engineering, New York. During that time he was the founder and director of Microprocessor Lab and VLSI Lab, leader of scientific projects and theses supervisor. From 1994 he was Assistant Professor of Computer Science and Director of Computer Center at University of Belgrade, from 2001 Associate Professor, Faculty of Mathematics, University of Belgrade, and from 2004 also a Professor of Computer Science and Dean of the College of Computer Science, Megatrend University Belgrade. He was teaching more than 20 graduate and undergraduate courses, from VLSI Design and Computer Architecture to Computer Networks, Operating Systems, Image Processing, Calculus and Queuing Theory. His research interest includes mathematical, queuing theory and heuristic optimizations applied to computer networks, image processing and combinatorial problems. Prof. Tuba is the author or coauthor of more than 150 scientific papers and coeditor or member of the editorial board or scientific committee of number of scientific journals and conferences. Member of the ACM, IEEE, AMS, SIAM, IFNA.

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