Genetic algorithms have established their capability for solving many complex optimization problems. Even as good solutions are produced, the user’s understanding of a problem is not necessarily improved, which can l...
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We propose a simple and optimal algorithm, BackMC, for local PageRank estimation in undirected graphs: given an arbitrary target node t in an undirected graph G comprising n nodes and m edges, BackMC accurately estima...
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optimization is employed in solutions of many problems today. optimization is described as finding the most suitable alternative among many others under the given constraints. Meta-heuristic algorithms used in solutio...
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ISBN:
(纸本)9781509004256
optimization is employed in solutions of many problems today. optimization is described as finding the most suitable alternative among many others under the given constraints. Meta-heuristic algorithms used in solutions of the problems are developed upon the behaviors of living creatures in the nature. One of these is Bat Algorithm (BA), an optimization method based on swarm intelligence. BA is a numerical optimization technique developed in recent times. In this paper, it is aimed at improving Bat Algorithm (IBA) by using Differential Evolution Algorithm population strategy instead of population generation method of BA. IBA was tested on 17 benchmark functions with different characteristics. Suggested method has been seen to exhibit better results compared to the original BA.
This article approaches about electrostatic discharge algorithm (ESDA) which is applied to find the optimization problems of economic load dispatch (ELD). This algorithm is tested and applied for the systems of 6 and ...
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ISBN:
(数字)9781728143620
ISBN:
(纸本)9781728143637
This article approaches about electrostatic discharge algorithm (ESDA) which is applied to find the optimization problems of economic load dispatch (ELD). This algorithm is tested and applied for the systems of 6 and 40 units. Wind power is included with the both systems for minimizing the cost. Now-a-days wind energy is getting more importance because wind energy is easily accessible all over the world. Both units of 6 and 40 are tested with and without wind energy respectively. The tested results are compared with the recent available optimization algorithms and electrostatic discharge algorithm proves itself as more effective optimization technique than others.
Population-based optimization algorithms are widely used in multiple research areas to optimize different kinds of problems. Commonly, they have been successfully applied to low and medium size search spaces in order ...
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ISBN:
(纸本)9781457702501
Population-based optimization algorithms are widely used in multiple research areas to optimize different kinds of problems. Commonly, they have been successfully applied to low and medium size search spaces in order to tune or adjust several design parameters. Unfortunately, population-based algorithms can require too much CPU time to find a nearly optimal solution as the number of dimensions of the problem to tackle increases significantly. Usually, mathematical or physical-inspired techniques have been applied to improve the success rate as well as the speed of convergence of population-based methods in a high dimensional framework. An alternative choice is to allocate the individuals of the population in an efficient way during the initialization stage of the algorithm considering two possibilities: placing individuals as close as possible to a global optimum or uniformly distributed over the search space. In this work, three different initialization strategies, the orthogonal array initialization, a chaotic technique and the opposition based initialization have been considered and appropriately combined with the heuristic particle swarm optimization (PSO) algorithm. Results comparing the modified PSO algorithm when applied to optimize frequency selective surfaces (FSS) and planar arrays for WiMAX applications are included.
One can recover vectors from Rm with arbitrary precision, using only ⌈log2(m+1)⌉+1 continuous measurements that are chosen adaptively. This surprising result is explained and discussed, and we present applications to ...
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Trajectory smoothing is an important step in robot motion planning, where optimization methods are usually employed. However, the optimization problem for trajectory smoothing in a clustered environment is highly non-...
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ISBN:
(纸本)9781509045839
Trajectory smoothing is an important step in robot motion planning, where optimization methods are usually employed. However, the optimization problem for trajectory smoothing in a clustered environment is highly non-convex, and is hard to solve in real time using conventional non-convex optimization solvers. This paper discusses a fast online optimization algorithm for trajectory smoothing, which transforms the original non-convex problem to a convex problem so that it can be solved efficiently online. The performance of the algorithm is illustrated in various cases, and is compared to that of conventional sequential quadratic programming (SQP). It is shown that the computation time is greatly reduced using the proposed algorithm.
In the last decades, inverse scattering problems have been faced by several stochastic methods with satisfactory results, thanks to their global optimization capabilities and their ability to take into account a-prior...
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ISBN:
(纸本)9781424420414
In the last decades, inverse scattering problems have been faced by several stochastic methods with satisfactory results, thanks to their global optimization capabilities and their ability to take into account a-priori information [1-3]. Nevertheless the computational burden required by these algorithms is often heavy. To overcome such a drawback, in this contribution a new hybrid approach is presented: a qualitative inversion technique is used to provide useful information about the location and shape of the scattering;these information are used to facilitate the convergence of a stochastic procedure, which is responsible for retrieving the point values of the dielectric permittivity. Namely, the proposed method consists of two steps: firstly the support of the scatterers is determined by the no-sampling Linear Sampling Method (nLSM), which is a fast inversion technique for visualizing the profile of a scatterer from measurements of the far-field data [4];then the dielectric parameters of interest are retrieved performing the minimization of a suitable cost function by means of an Ant Colony optimization algorithm (ACO). ACO is a recently introduced stochastic optimization algorithm, inspired by social behavior of ant colonies, to solve hard minimization problems [5,6]. In this paper the described technique will be applied to TM two-dimensional inverse scattering problems. The input data of this approach is the far-field matrix whose ij-entry is the far-field sample u{sub}∞(x{sub}i, d{sub}j) measured in the direction x{sub}i when the targets are illuminated by a plane wave impinging from direction d{sub}j.
The way heuristic optimizers are designed has evolved over the decades, as computing power has increased. Such has been the case for the Linear Ordering Problem (LOP), a field in which trajectory-based strategies led ...
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Two global optimization problems with high dimensionality and many local minima are investigated with two different optimization algorithms: DIRECT and simulated annealing. The problems include a difficult biomechanic...
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ISBN:
(纸本)9781617828409
Two global optimization problems with high dimensionality and many local minima are investigated with two different optimization algorithms: DIRECT and simulated annealing. The problems include a difficult biomechanics problem with a great deal of experimental noise and a deterministic integer programming problem with a known global minimum.
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