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The Increasing demand of cellular communication services and limited frequency spectrum leads to a NP hard dilemma of channel allocation. Most of the existing channel allocation techniques are Dynamic Channel Allocation based on various optimization algorithms, minimizing the call blocking probability by desolating electromagnetic compatibility constraints, which produces significant interferences...
In this paper, a relevant document retrieval method is proposed for document retrieval systems with vector space models (VSM). In recent years, with the size of the database becomes extremely large, there becomes a high demanding of an accurate and fast-time document retrieval algorithm. Based on the maximum similarity criterion, a document retrieval algorithm using the discrete stochastic optimization...
Reviewing the present situation and existence questions of environment protection technology at home and abroad and pointing out that the use of modern information technology to control ecological consumption and economic benefits in highway planning stage, Implementing the natural ecological environment protection and vegetation restoration measures in the stage of design and construction, while...
The process of selecting which virtual machines will be placed (i.e. executed) in the physical machines available in a Datacenter is known as virtual machine placement problem. This work proposes for the first time a formulation of the problem, with a multi-objective approach, of the main objective functions studied so far as mono-objective in the state of the art. Also it is proposed a multi-objective...
A network design is robust if it is able to deal with any traffic requirement under certain bounds and physical network conditions. The robust network design is a complex problem of growing importance where, in general, the only information available are traffic bounds of the network links. This work proposes a Genetic Algorithm to design robust networks with optimal capacity of links considering...
Mathematical morphology is a formalism largely used in image processing for implementing many different tasks. Several operators that support the formalism have also been successfully used for inducing data clusters. Particularly, the Binary Morphology Clustering Algorithm (BMCA) is one of such inductive methods which, given a set of input patterns and morphological operators, produces clusters of...
In this paper, the problem of antenna array failure has been addressed using Differential Evolution (DE) Algorithm by controlling only the amplitude excitation of array elements. A fitness function has been formulated to obtain the error between pre-failed pattern and measured pattern and this function has been minimized using DE. Numerical example of large number of element failure has been considered...
This paper provides a brief description on how continuous algorithms can be applied to binary problems. Differential Evolution is the continuous algorithm studied and two versions of this algorithm are presented: the Binary Differential Evolution with a binary encoding and the Discretized Differential Evolution with a continuous encoding. Several discretization methods are presented and the most used...
Within functional verification of digital systems there are dynamic methods based on Device Under Verification simulation. We focus on this type of method using functional coverage points. Nowadays, the main problem consists in obtaining high values to exercise all functional coverage points in the device. In this paper we propose a heuristic dynamic verification method based on a Binary Differential...
A recent nature inspired optimization algorithm, Fish School Search (FSS) is applied to the finite element model (FEM) updating problem. This method is tested on a GARTEUR SM-AG19 aeroplane structure. The results of this algorithm are compared with two other metaheuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). It is observed that on average, the FSS and PSO algorithms...
The purpose of this work is to apply a hybrid algorithm based on Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) for solving the problem of Economic Dispatch, which is based on supplying an energy demand, subjected to some restriction and reach out the best possible cost. Basically, we use the mutation operator from GAs aiming to explore regions in the search space that cannot be reached...
This paper introduces a new approach to building sparse least square support vector machines (LSSVM) based on genetic algorithms (GAs) for classification tasks. LSSVM classifiers are an alternative to SVM ones due to the training process of LSSVM classifiers only requires to solve a linear equation system instead of a quadratic programming optimization problem. However, the lost of sparseness in the...
The multicast rate of satellite communication networks (SCN) can be maximized by using randomized network coding (RNC). To optimize the RNC-based multicast for SCN, the number of coding links should be minimized to reduce the computational complexity on satellite, while the dynamic topology needs to be considered. To this end, in this paper, we propose an improved genetic algorithm (IGA) to minimize...
This paper studies the initial orbit determination based on sparse space-based angle measurement and genetic algorithm. The double rho iteration model used by the space-based initial orbit determination is briefly introduced firstly. Because of problems of iteration divergences and self-solutions in the space-based initial orbit determination, the genetic algorithm of SGA and MPGA are then adopted...
A new plane parallel micro-manipulator is presented in this paper, together with the numerical procedure that has been used in order to optimize some kinetostatic performance indices, among which the kinematic condition number and the mechanical advantage. The approach is based on a refined simplification of the direct kinematic problem and it is applied to the pseudo-rigid body model of the original...
The genetic algorithms (GAs), as the optimization methods, are expansively used in mobile robot techniques. In this paper a previously developed, multi-agent based map building process optimizing GA [1] will be revised in form of GA algorithm optimization and GA's parameter tuning. The results of the algorithm-improving will be compared and analyzed in the conclusion.
Nowadays there is a vast amount of IT tools specialized in vector graphics. The data generated by those tools could be used to describe the path of industrial manipulators as a set of vectors. The main problem is that the sequence/direction of those vectors is not meant to be executed by a robot and attempting to do it, would result in inefficient cycle times of the robot. Therefore it is necessary...
In this paper, an improved version of compact Genetic Algorithm (M-cGA) is proposed for thinned array synthesis. By adding suitable learning scheme between probability vectors (PVs), improved cGA can effectively control the peak sidelobe (PSL) of thinned arrays. Its performances have been compared with those of a Genetic Algorthim, used alone or in conjunction with the Almost Different Set (ADS) for...
Web services are a popular choice for component oriented systems that support dynamic compositions. Automated negotiation among Web services provides an effective way for the services to bargain for their optimal customizations and allows the discovery of overlooked potential solutions. Unique and dynamic Quality of Service (QoS) requirements of service consumers pose challenges for effective approaches...
In this paper, we describe an optimization method based on differential evolution (DE). It shows good convergence properties with few parameters. However, the appropriate selection of the parameters is a difficult task. Hence, we here analyze the performance indexes of the DE algorithm to set the control parameters. Moreover, to identify the best parameter intervals, the DE approach is first compared...
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