Journal ArticleDOI
Spider Monkey Optimization: A Novel Technique for Antenna Optimization
TLDR
The SMO is a new swarm intelligence technique that models the foraging behavior of spider monkeys that is used to synthesize the array factor of a linear antenna array and to optimally design an E-shaped patch antenna for wireless applications.Abstract:
The aim of this letter is to introduce and use the spider monkey optimization (SMO) as an optimization technique for the electromagnetics and antenna communities. The SMO is a new swarm intelligence technique that models the foraging behavior of spider monkeys. To show the efficiency of the SMO, different examples are presented, and the results are compared to the results obtained using other popular optimization techniques. The optimization procedure is used to synthesize the array factor of a linear antenna array and to optimally design an E-shaped patch antenna for wireless applications. By comparing to traditional optimization techniques reported in the literature, it is evident that SMO is efficient in reaching the optimum solutions with less number of experiments .read more
Citations
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Journal ArticleDOI
Discrete Spider Monkey Optimization for Travelling Salesman Problem
TL;DR: An effective variant of SMO to solve TSP called discrete SMO (DSMO), where every spider monkey represents a TSP solution where Swap Sequence and Swap Operator based operations are employed, which enables interaction among monkeys in obtaining the optimal T SP solution.
Book ChapterDOI
Spider Monkey Optimization Algorithm
TL;DR: This chapter presents the Spider Monkey Optimization algorithm in detail and a numerical example of SMO procedure has also been given for a better understanding of its working.
Journal ArticleDOI
A boolean spider monkey optimization based energy efficient clustering approach for WSNs
TL;DR: A SMO based threshold-sensitive energy-efficient clustering protocol is proposed to prolong network lifetime with an intend to extend the stability period of the network and demonstrates that the proposed protocol significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.
Introduction to Genetic Algorithms in Electromagnetics
Randy L. Haupt,Brian J. Barbisch,Douglas H. Werner,Pingjuan L. Werner,Dianel Erni,Dorthea Wiesmann,Michael Spühler,Stephan Hunziker,Esteban Moreno,Neil N. Jackson,Peter S. Excell,D.S. Linden,R. MacMillan,Sue Ellen Haupt,Luciano Tarricone,G. H. Smith,P. R. Williamson,K. Vozoff,Y. Ji,Hao Wang,Todd H. Hubing,F. Tiezzi,Alejandro Alvarez-Melcon,Juan R. Mosig +23 more
TL;DR: This article is a tutorial on using genetic algorithms to optimize antenna and scattering patterns, and provides a detailed explanation of how a genetic algorithm works, and a listing of a MATLAB code.
Journal ArticleDOI
The Grey Wolf Optimizer and Its Applications in Electromagnetics
Xun Li,Kwai-Man Luk +1 more
TL;DR: The results show that the GWO is capable of outperforming or providing very competitive results compared with some well-known metaheuristics such as the genetic algorithm, particle swarm optimization, and differential evolution, and may serve as a promising candidate for handling electromagnetic problems.
References
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Journal ArticleDOI
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
TL;DR: Different models of genetic operators and some mechanisms available for studying the behaviour of this type of genetic algorithms are revised and compared.
Journal ArticleDOI
An introduction to genetic algorithms for electromagnetics
TL;DR: In this paper, a tutorial on using genetic algorithms to optimize antenna and scattering patterns is presented, and three examples demonstrate how to optimize antennas and backscattering radar-cross-section patterns.
Journal ArticleDOI
Linear array geometry synthesis with minimum sidelobe level and null control using particle swarm optimization
TL;DR: This paper describes the synthesis method of linear array geometry with minimum sidelobe level and null control using the particle swarm optimization (PSO) algorithm, a newly discovered, high-performance evolutionary algorithm capable of solving general N-dimensional, linear and nonlinear optimization problems.
Journal ArticleDOI
Spider Monkey Optimization algorithm for numerical optimization
TL;DR: The proposed swarm intelligence approach is named as Spider Monkey Optimization (SMO) algorithm and can broadly be classified as an algorithm inspired by intelligent foraging behavior of fission–fusion social structure based animals.
Journal ArticleDOI
Parallel particle swarm optimization and finite- difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designs
Nanbo Jin,Yahya Rahmat-Samii +1 more
TL;DR: This paper presents a novel evolutionary optimization methodology for multiband and wide-band patch antenna designs that combines the particle swarm optimization and the finite-difference time-domain to achieve the optimum antenna satisfying a certain design criterion.