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MAX-SAT is a classic NP-hard optimization problem. Many real problems can be easily represented in, or reduced to MAX-SAT, and thus it has many applications. Finding optimum solutions of NP-hard optimization problems using limited computational resources seems infeasible in general. In particular, all known exact algorithms for MAX-SAT require worst-case exponential time, so evolutionary algorithms...
In practical distributed storage networks, data centres house hundreds of racks, each of which contains several storage nodes. However, the majority of works in distributed storage assume a simple network model with a collection of identical storage nodes with same communication cost between the nodes. In this paper, we consider a more realistic rack model of storage network and present a code design...
The power conversion from variable AC voltage into a desired AC voltage with fixed magnitude and fixed frequency is attracting more attention especially in case of grid-connected wind generation system. Indeed, the Direct Matrix Converter (DMC) can be used as a suitable solution for such AC/AC conversion to fulfill the requirement of the output voltage with desired magnitude and frequency. This paper...
A new technique is introduced for evaluating the vector potential of circular loop antennas (CLAs) with arbitrary current distribution and dimensions, which can be used to obtain the exact electromagnetic fields in near and far regions of the antenna. The technique is based on the spherical Bessel functions (SBFs) and associated Legendre polynomials (ALPs) expansion. This expansion is used to decouple...
The spherical vector wave functions are investigated for strong chiral medium. The electromagnetic (EM) resonance in the spherical cavity with perfect electric conductor (PEC) wall, filled with strong chiral medium, is studied. The method for the investigation of frequencies at which the resonance occur is discussed using the characteristic equation of spherical cavity filled with strong chiral medium...
In this paper, an aircraft roll control system based on design an autopilot that controls the roll angle of an aircraft is modeled using Matlab/Simulink. Firstly, modeling phase begins with a derivation of suitable mathematical model to describe the lateral directional motion of an aircraft. Then, the Linear Quadratic Controller (LQR) and Fuzzy Logic Controller (FLC) are developed for controlling...
This paper discusses the aerodynamics characteristics of Blended Wing Body — Baseline II E2, unmanned aerial vehicle aircraft. A computational method, Computational Fluid Dynamic (CFD) Star CCM+ software has been performed to obtain the aerodynamics characteristic of the BWB. The aerodynamic characteristics prediction of BWB-Baseline II E2 aircraft was obtained through CFD analysis using unstructured...
Quantum Evolutionary Algorithm (QEA) is an optimization algorithm based on the concept of quantum computing and Particle Swarm Optimization (PSO) algorithm is a population based intelligent search technique. Both these techniques have good performance to solve optimization problems. PSEQEA combines the PSO with QEA to improve the performance of QEA and it can solve single objective optimization problem...
In the present study we propose a new hybrid version of differential evolution (DE) and particle swarm optimization (PSO) algorithms. In the proposed algorithm named as hybrid differential evolution (HDE) a `switchover constant' called ?? is defined. HDE starts as the basic DE algorithm which switches over to PSO when ?? is activated. The constant ?? on the other hand is activated at a point where...
Optimization problems are ubiquitous and consequential. In fact every sphere of human activity that can be quantified can be formulated as an optimization problem. The focus of this work is on Global Optimization which is not only desirable but also necessary in many cases. In the past few decades several Global optimization algorithms have been suggested in literature out of which stochastic, population...
Differential Evolution (DE) is generally considered as a reliable, accurate and robust optimization technique. However, the algorithm suffers from slow convergence rate and takes large computational time for optimizing the computationally expensive objective functions. Therefore, an attempt to speed up DE is considered necessary. This research introduces a modified differential evolution, called Ant...
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