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International Conference on Advances in Mechanical, Industrial, Automation and Management Systems (AMIAMS)

作者： Dutta, Pooja Datta, Dilip Tezpur Univ Dept Mech Engn Napaam 784028 Tezpur India

ISBN: (纸本)9781509056743

The bi-level problem is an embedded decentralized optimization process at two levels arisen in hierarchy-based organizations. The activities of the lower-level are governed by the upper-level, while the performance of the latter is dependent upon that of the former. Though consists of two decentralized levels, their embedding nature makes the solution procedure of the bi-level problem complicated. In the present work, a multi-objective differential evolution algorithm is employed to solve this problem as a plain multi-objective optimization problem by combining its two levels. The proposed procedure is found very potential in identifying promising trade-off optimal solutions for a number of benchmark problems.

关键词： Bi-level Multi-Objective hierarchy-based Benchmark testing plains Decentralized Optimization Procedure optimal solution embedding differential evolution algorithms

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An Adaptive Strategy to Adjust the Components of Memetic algorithms 26

An Adaptive Strategy to Adjust the Components of Memetic Alg...

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26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Xu, Jin Cai, Zhihua Gong, Wenyin China Univ Geosci Dept Comp Sci Wuhan 430074 Peoples R China

ISBN: (纸本)9781479965731

Memetic algorithms(MAs) represent one of the promising areas of evolutionary algorithms. However, there are many issues to be solved to design a robust MA. In this paper, we introduce an adaptive memetic algorithm, named GADEDHC, which combines a genetic algorithm and a differential evolution algorithm as global search methods with a directional hill climbing(DHC) algorithm as local search method. In addition, a novel strategy is proposed to balance the intensity of global search methods and local search method, as well as the ratio between genetic algorithm and differential evolution algorithm. Experiments on several benchmark problems of diverse complexities have shown that the new approach is able to provide highly competitive results compared with other algorithms.

关键词： Algorithm design and analysis Benchmark testing Genetic algorithms Memetics Search methods Sociology Statistics Search methods Benchmark testing Algorithm design and analysis Genetic Algorithm (GA) Sociology differential evolution algorithms

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Optimization and Design of a Wideband Vertically Stacked Yagi-Uda Antenna Array with a Wide Azimuth HPBW

Optimization and Design of a Wideband Vertically Stacked Yag...

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10th International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Yuan, Jiantao Fu, Guang Lei, Juan Luo, Yong Xidian Univ Natl Key Lab Antennas & Microwave Technol Xian 710071 Peoples R China

ISBN: (纸本)9781467318006

A vertically stacked Yagi-Uda antenna array with X-shape driven dipoles for the long range Meteor Burst Communication(MBC) at the VHF is presented using differential evolution algorithm (DE). In order to illustrate the capabilities of the method, a 3-element Yagi-Uda antenna array is given. The measured and simulated impedance bandwidth of VSWR<1.4 reaches 22% and some solved methods are proposed to cope with the demand from wide azimuth HPBW. The results show that the simulated antenna gain across the operating frequency band is 8.1 similar to 8.3dB and the HPBW in the azimuth plane is above 90 degrees.

关键词： Yagi antenna azimuth plane operating frequency band azimuth antenna gain differential evolution algorithms dipoles broadband

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Stochastic Optimal Dispatch of Power System Under Extreme Weather Disaster

Stochastic Optimal Dispatch of Power System Under Extreme We...

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International Conference on Engineering Design and Optimization (ICEDO 2010)

作者： Zhang, Yongxi Yang, Hongming Dong, Zhaoyang Lai, Mingyong Changsha Univ Sci & Technol Changsha 410114 Hunan Peoples R China Hong Kong Polytech Univ Hong Kong Peoples R China Hunan Univ Changsha 410079 Peoples R China

ISBN: (纸本)9780878492220

Several large scale failures of power system took place due to extreme weather disaster recent years, which aroused the consideration of power network security operation. Considering that the line failure events caused by natural disaster presented random characteristic, using Poisson distribution theory to depict the probability of line failure, a stochastic power system optimal dispatch model based on chance constraints theory was also proposed. We adopted the differential evolution algorithm to calculate the total loss based on Monte-Carlo simulation. The results of IEEE 9-bus case study imply that the dispatch model will give full consideration of weather effects, and provide a more reasonable dispatch plan for power system disaster prevention and reduction.

关键词： differential evolution algorithms Extreme weather disaster Stochastic optimal dispatch

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Optimal PID Controller for Ball and Beam System

Optimal PID Controller for Ball and Beam System

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IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

作者： Prasad, K. T. Hote, Y. V. Indian Inst Technol Dept Elect Engn Roorkee 247667 Uttar Pradesh India

ISBN: (纸本)9781479940400

In this paper, PID controller is designed for Ball and Beam system using Genetic Algorithm and differential evolution. The analysis shows that the differential evolution algorithm is better in comparison to Genetic algorithm with respect to speed of convergence and performance index. Further, it is also observed that the controller design based on differential evolution shows faster disturbance rejection in comparison to Genetic algorithm. All the results are simulated in MatIab environment.

关键词： Ball Device Component Proportional Integral Derivative Control Genetic Algorithm (GA) beam system controller design differential evolution algorithms Disturbance rejection performance indicators evolutionary algorithm Converge

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An Optimal Radial Layout for High Dimensional Data Class Visualization

An Optimal Radial Layout for High Dimensional Data Class Vis...

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International Conference on Advanced Technologies for communications (ATC)

作者： Tran Van Long Vu Thi Ngan Univ Transport & Commun Fac Basic Sci Hanoi Vietnam Hanoi Coll Commerce & Tourism Fac Basic Sci Ha Noi City Vietnam

ISBN: (纸本)9781467383745

Multivariate data visualization is an interesting research field with many applications in ubiquitous fields of sciences. Radial visualization is one of the most common information visualization techniques for visualizing multivariate data. Unfortunately, Radial visualization display different information about structures of multivariate data on the different positions of dimensional anchors on the unit circle. In this paper, we propose a method that improve the Radviz layout for class visualization of high-dimensional data. We apply the differential evolution algorithm to find the optimal dimensional anchors of the RadViz such that maximum the quality of Radial visualization for classifier data. We use the k nearest neighbors classifier for quality measurement. Our method provides an improvement visualizing class structures of high-dimensional data sets on the RadViz. We demonstrate the efficiency of our method for some data sets.

关键词： dimensional data Visualization Unit circle k nearest neighbor Radial Data visualisation Quality management differential evolution algorithms information visualization layouts Boat anchors Multivariate

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A Population Adaptation Mechanism for differential evolution Algorithm

A Population Adaptation Mechanism for Differential Evolution...

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IEEE Symposium Series on Computational Intelligence

作者： Johanna Aalto Jouni Lampinen Dept. of Comput. Sci. Univ. of Vaasa Vaasa Finland

ISBN: (纸本)9781479975617

In the original differential evolution algorithm three different control parameter values must be pre-specified by a user. These parameters are the population size, the crossover constant and the mutation scale factor. Control parameters affect strongly the performance and reliability of the algorithm. However, choosing good parameters can be very difficult for a user. In this paper a new adaptive differential evolution algorithm called Cumu-DE is proposed. The aim of the algorithm is to be a user friendly and reliable algorithm with moderate convergence speed. In the proposed algorithm, the so called effective population size is adapted automatically using mechanism based on probability mass function. The actual population size is kept fixed. Even though we talk about two different population sizes, we have only one population. The effective population size describes the effective part of the actual population. The more we get successful trials, the smaller the effective population is and vice versa. The algorithm was initially evaluated by using the set of 25 benchmark functions provided by CEC2005 special session on real-parameter optimization. It was compared with the results of standard DE/rand/1/bin. The proposed algorithm Cumu-DE proved to be significantly faster due to its average of FES in four cases and significantly slower in six cases. Additionally, Cumu-DE was significantly more reliable in six cases and significantly less reliable in none. These results are demonstrating the potential of the proposed adaptation approach.

关键词： differential evolution algorithms population size evolutionary algorithm control parameter effective population size Parameter optimization FES gene algorithms

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Automatic Column Grouping of 3D Steel Frames via Multi-Objective Structural Optimization

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BUILDINGS 2024年第1期14卷 191-191页

作者： Resende, Claudio Martha, Luiz Fernando Lemonge, Afonso Hallak, Patricia Carvalho, Jose Motta, Julia Pontifical Catholic Univ Rio de Janeiro Postgrad Program Civil & Environm Engn BR-22451900 Rio De Janeiro Brazil Pontifical Catholic Univ Rio de Janeiro Dept Civil & Environm Engn BR-22451900 Rio De Janeiro Brazil Univ Fed Juiz de Fora Sch Engn Dept Appl & Computat Mech BR-36036900 Juiz De Fora Brazil Univ Fed Rio de Janeiro Civil Engn Program Coordinat Postgrad Programs Engn COPPE BR-21941909 Rio De Janeiro Brazil Univ Fed Juiz de Fora Civil Engn Program BR-36036900 Juiz De Fora Brazil

Formulations of structural optimization problems are proposed in this paper to automatically find the best grouping of columns in 3D steel buildings. In these formulations, the conflicting objective functions, minimized simultaneously, are the weight of the structure and the number of different groups of columns. In other words, the smaller the number of different groups of columns, the greater the weight of the structure, and the greater the number of groups, the smaller the structure's weight. The design variables are the bracing system configuration, column cross-section orientation, and assigned W-shaped profile indices for columns, beams, and braces. The design constraints are the allowable displacements, strength, and geometric considerations. After solving the multi-objective optimization problem, the result is a Pareto front, presenting non-dominated solutions. Three evolutionary algorithms based on differential evolution are adopted in this paper to solve three computational experiments. Even if preliminary groupings of columns are adopted, considering architectural aspects such as the symmetry of the structure, it is possible to discover other interesting structural configurations that will be available to the decision maker, who will be able to make their choices based on the impacts on manufacturing, cutting, transporting, checking and welding.

关键词： automatic member grouping multi-objective optimization steel frames differential evolution algorithms

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Inverse-designed terahertz modulators based on semiconductor multilayers

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SEMICONDUCTOR SCIENCE AND TECHNOLOGY 2021年第8期36卷

作者： Centeno, E. Alvear-Cabezon, E. Smaali, R. Moreau, A. Taliercio, T. Univ Clermont Auvergne CNRS SIGMA Clermont Inst Pascal F-63000 Clermont Ferrand France Univ Montpellier IES UMR CNRS 5214 Montpellier France

Using a global optimization algorithm, differential evolution, we show that optically actuated terahertz (THz) modulators can be designed using multilayers of InAs and GaSb semiconductors. The optical pump is actually able to generate photocarriers which diffuse into the structure and drastically modify its response at THz frequencies. A modulation depth between 63% and 85% is reached in the range of 1-3 THz for a low pump irradiance of 10 W cm(-2) in the continuous regime, whether the modulators operate at one or up to four arbitrary chosen frequencies.

关键词： terahertz modulator photogeneration differential evolution algorithms

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QANA: Quantum-based avian navigation optimizer algorithm

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2021年 104卷 104314-104314页

作者： Zamani, Hoda Nadimi-Shahraki, Mohammad H. Gandomi, Amir H. Islamic Azad Univ Fac Comp Engn Najafabad Branch Najafabad Iran Islamic Azad Univ Big Data Res Ctr Najafabad Branch Najafabad Iran Univ Technol Sydney Fac Engn & Informat Technol Ultimo NSW Australia

differential evolution is an effective and practical approach that is widely applied for solving global optimization problems. Nevertheless, its effectiveness and scalability are decreased when the problems' dimension is increased. Hence, this paper is devoted to proposing a novel DE algorithm named quantum-based avian navigation optimizer algorithm (QANA) inspired by the extraordinary precision navigation of migratory birds during long-distance aerial paths. In the QANA, the population is distributed by partitioning into mull flocks to explore the search space effectively using proposed self-adaptive quantum orientation and quantum-based navigation consisted of two mutation strategies, DE/quantum/I and DE/quantum/II. Except for the first iteration, each flock is assigned using an introduced success-based population distribution (SPD) policy to one of the quantum mutation strategies. Meanwhile, the information flow is shared through the population using a new communication topology named V-echelon. Furthermore, we introduce two long-term and short-term memories to provide meaningful knowledge for partial landscape analysis and a qubit-crossover operator to generate the next search agents. The effectiveness and scalability of the proposed QANA were extensively evaluated using benchmark functions CEC 2018 and CEC 2013 as LSGO problems. The results were statistically analyzed by the Wilcoxon signed-rank sum test, ANOVA, and mean absolute error tests. Finally, the applicability of the QANA to solve real-world problems was evaluated by four engineering problems. The experimental results and statistical analysis prove that the QANA is superior to the competitor DE and swarm intelligence algorithms in test functions CEC 2018 and CEC 2013, with overall effectiveness of 80.46% and 73.33%, respectively.

关键词： Optimization Metaheuristic algorithms differential evolution algorithms Topology Large-scale global optimization Quantum computing Engineering optimization problems

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