Notice of Violation of IEEE Publication Principles - Non-uniform circular-shaped antenna array design and synthesis — A Multi-Objective Evolutionary approach

Abstract

Notice of Violation of IEEE Publication Principles<br><br>"Non-uniform circular-shaped antenna array design and synthesis — A Multi-Objective Evolutionary approach"<br><br>by Jubin Hazra<br>in the International Conference on Computer Communication and Informatics (ICCCI), 2012, pp. 1 – 4<br><br>After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.<br><br>This paper contains significant portions of original text from the paper cited below. The original text was copied with insufficient attribution (including appropriate references to the original author(s) and/or paper title) and without permission.<br><br>Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:<br><br>"Non-uniform Circular-Shaped Antenna Array Design and Synthesis - A Multi-Objective Approach"<br>by Saurav Ghosh, Subhrajit Roy, Sk. Minhazul Islam , Shizheng Zhao, Ponnuthurai Nagaratnam Suganthan, and Swagatam Das<br>in the Lecture Notes in Computer Science, Volume 7077, Swarm, Evolutionary, and Memetic Computing, 2011, pp. 223 – 230<br><br> <br/> Design of non-uniform circular antenna arrays is one of the important optimization problems in electromagnetic domain. While designing a non-uniform circular array the goal of the designer is to achieve minimum side lobe levels with maximum directivity. In contrast to the single-objective methods that attempt to minimize a weighted sum of the four objectives considered here, in this article we consider these as four distinct objectives that are to be optimized simultaneously in a multi-objective (MO) framework using one of the best known Multi-Objective Evolutionary Algorithms (MOEAs) called NSGA-II. This MO approach provides greater flexibility in design by producing a set of final solutions with different trade-offs among the four objective from which the designer can choose one as per requirements. To the best of our knowledge, other than the single objective approaches, no MOEA has been applied to design a non-uniform circular array before. Simulations have been conducted to show that the best compromise solution obtained by NSGA-II is far better than the best results achieved by the single objective approaches by using the differential evolution (DE) algorithm and the Particle Swarm Optimization (PSO) algorithm.