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In this paper, Hybrid Taguchi Genetic Algorithm (HTGA) is used to minimize the side lobe level and to keep half power beam width in certain values for cylindrical conformal antenna array. The HTGA is based on Genetic Algorithm (GA) and Taguchi Algorithm (TA). Results obtained by GA, TA and HTGA are compared. The best results are also compared with the results obtained by HFSS (High Frequency Structural...
The most powerful metaheuristics must be good at both exploitation and exploration. In the present day, metaheuristics are designed to reach a balance between these two capabilities for the sake of avoiding being trapped in the local optimum or unable to achieve convergence. For the first time in history, it is noteworthy that exploitation and exploration are both strong in the use of the Jaguar Algorithm...
This paper presents a recently developed algorithm based on the emulation of decision making process in social network environments, called Social Network Optimization (SNO). The design of a sparse array is here addressed in order to assess SNO's performance on a benchmark EM optimization problem. Reported results show its effectiveness in dealing with EM problems.
This paper proposes solution to optimize the peak side lobes level (PSLL) in a distributed random antenna array (RAA) when locations of the nodes in the array cannot be manipulated. Using the conventional beam forming method, RAA produces a poor beam pattern with high side lobe level, which greatly reduces the performance and the efficiency of the antenna. Existing literature focuses on finding the...
Considerable portion of water distribution cost is related to energy usage. Pumps are often the greatest energy consumer in water distribution systems. Optimizing the working schedule of these pumps has the potential to significantly decrease operation costs of these systems. It is also possible to optimize for environmental concerns and arrive at the least polluting solution of pump operation that...
Collaborate beamforming in wireless sensor networks (WSNs) is a concept of using beamforming technology to establish link in the networks. It can effectively increase the transmission distance and improve the energy efficiency of the networks. Due to random deployment of the sensor nodes in the networks, proper assignment for the sensor nodes in wireless sensor networks is vital to achieve better...
This paper investigates the influence of different crossover operators on the efficiency of the hybrid Taguchi genetic algorithm and aims to provide guidelines for algorithm's usage in continuous optimization. We examine the hybrid Taguchi genetic algorithm (HTGA) with 8 different crossover operators and apply it to 15 benchmark numerical optimization problems. The implementation uses binary representation...
Antenna array systems are important components of modern radar and wireless communication systems. By controlling the array through a real-time optimization process, the adaptive techniques diminish the impact of system component noise and mitigate the effects of interfering radiation to ensure the delivery of a maximum fidelity signal. This paper deals with the possibilities to cancel unwanted signals...
In this paper the design problem of an equi-spaced linear array is considered with the constraint of reducing side lobe level which results in the leakage of the received signal energy. In order to achieve this, powerful tool based on the event of probability has to be chosen. We consider an evolutionary approach, which avoids the adaptive nature and avails the tuning mechanism. Genetic Algorithm...
In this paper synthesis of symmetric linear antenna arrays is described using Genetic Algorithm (GA). Genetic Algorithm has many advantages over other conventional optimization techniques. Real coded GA (RGA) is a high performance evolutionary optimization algorithm. It is used in this paper to find optimum inter-element spacing and excitation coefficients for the symmetric linear antenna array in...
Six primary factors have been analyzed which influence the performance of the Genetic Algorithm. The concrete method has been designed of setting algorithm parameters by using multi-factor analysis of variance. And it illustrates the implementation process of the methods by specific examples of applications. In the end with the data gained from the experiment it has proved that the performance of...
Genetic Algorithms(GAs) are suitable for parallel computing since population members fitness maybe evaluated in parallel. Most past parallel GA studies have exploited this aspect, besides resorting to different algorithms, such as island, single-population master-slave, fine-grained and hybrid models. A GA involves a number of other operations which, if parallelized, may lead to better parallel GA...
Antenna designers are constantly challenged with the temptation to search for optimum solutions for the design of complex electromagnetic devices. The ability of using numerical methods to accurately and efficiently characterizing the relative quality of a particular design has excited the engineers to apply stochastic global evolutionary optimizers for this objective. Evolutionary techniques have...
A new approach for the synthesis of thinned linear array with minimum sidelobe level is introduced. The method is a genetic algorithm based on orthogonal design. The orthogonal design with the factor analysis, an experimental design method, is applied to the genetic algorithm, to make the algorithm be more robust, statistically sound and quickly convergent. In order to evaluate the performance of...
Given a linear antenna array with an excitation distribution affording an optimal sum pattern, subarray weighting allows the same array also to generate a difference pattern, with minimal alteration of the signal feed circuitry. Previous implementations of this approach have considered the whole array for subarraying. Here we report that the required feeding networks can be further simplified by keeping...
In this paper the comparative optimal designs for maximum sidelobe level (SLL) reduction of three-ring concentric circular antenna array (CCAA) are determined using two novel Particle Swarm Optimization (PSO) techniques namely Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSOCFIWA), Craziness based Particle Swarm Optimization (CRPSO) and Binary coded Genetic Algorithm...
In this paper we propose a novel genetic algorithm called immunity genetic algorithm (IGA) based on stochastic crossover evolution to solve the synthesis problem of thinned arrays. Our crossover operator is a variant of the known GA operator. A new expression of the array factor for a specific number of elements N is expressed as a linear discrete cosine transform (DCT). Using IGA to generate thousands...
Beam forming systems using adaptive array antennas are a viable solution to a number of problems in applications related to mobile communications. Genetic Algorithms and Particle Swarm Optimization have been extensively used in electromagnetic optimization and antenna design problems. In this paper two smart antennas are investigated, with the purpose to determine the appropriate configuration for...
The goal of this paper is to optimize the array weighting in order to minimize the sidelobe level (SLL) of the phased array antenna without losing the beam width. The simulated antenna is linear array with 8 and 10 elements. Genetic algorithm has been used for the optimization process. The weights chosen to meet any specific criteria, the criterion is to minimize the sidelobe level with narrow beam...
This paper presents a hybrid evolutionary algorithm to solve mixed-integer nonlinear bilevel programming problems, in which integer decision variables are controlled by an upper-level decision maker and real-value (continuous) decision variables are controlled by a lower-level decision maker. This hybrid evolutionary algorithm contains the mutation operator used in the differential evolution, the...
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