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检索条件"主题词=Optimization algorithms"

共 4005 条记录，以下是3131-3140 订阅

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Computer Aided Design, Analysis, optimization and Manufacturing of Switched Reluctance Machine

Computer Aided Design, Analysis, Optimization and Manufactur...

引用

International Conference on Electrical Machines and Systems (ICEMS)

作者： Song Shoujun Xia Zekun Chen Shuo Sun Runyu Wang Qingyu Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China

ISBN: (纸本)9781479914463;9781479914470

In this paper, the computer aided design, analysis, optimization and manufacturing processes of switched reluctance machine (SRM) with a piece of self-developed software are detailed presented. According to the performance requirements, the physical dimensions of stator and rotor laminations are obtained by two traditional methods. Then, the electromagnetic characteristics and operating performances of the designed SRM are calculated by magnetic equivalent circuit (MEC), and optimization algorithms, such as genetic algorithm (GA), are applied to enhance certain performance indexes. Finally, for convenience of manufacturing, the machining drawings of the designed SRM are generated as well.

关键词： switched reluctance machine Reluctance motors Computer-Aided Design Genetic Algorithm (GA) standard reference materials optimization algorithms Manufacturing process piecing manufacturing operating performance

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An Ant Colony optimization Algorithm and Multi-Agent System Combined Method to Solve Single Source Capacitated Facility Location Problem

An Ant Colony Optimization Algorithm and Multi-Agent System ...

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6th International Conference on Advanced Computational Intelligence (ICACI)

作者： Yang, Lina Sun, Xu Chi, Tianhe Chinese Acad Sci Inst Remote Sensing & Digital Earth Beijing Peoples R China

ISBN: (纸本)9781467363433

ACO is an effective method to solve Single Source Capacitated Facility Location Problem (SSCFLP). However, the increasing data size will cause its decreasing computing efficiency. Based on Agent-Oriented Programming (AOP) paradigm to build a distributed Multi-Agent System of ACO to solve SSCFLP is an efficient way of reducing computing time. This method is tested in three comparative experiments under two different data size condition, which proves that using multiple computers to build MAS can greatly improve the efficiency of intelligent computing.

关键词： Multi-agent systems ADMINISTRATIVE CONSENT ORDER data size facility location multicomputer Solve Combined Method optimization algorithms Ant colony optimization magic angle spinning

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optimization OF A CENTRIFUGAL COMPRESSOR IMPELLER DESIGN FOR ROBUSTNESS TO MANUFACTURING UNCERTAINTIES

引用

ASME Turbo Expo: Turbine Technical Conference and Exposition

作者： Javed, A. Pecnik, R. van Buijtenen, J. P. Delft Univ Technol Proc & Energy Dept NL-2628 CA Delft Netherlands

ISBN: (纸本)9780791855195

Compressor impellers for mass-market turbochargers are die-casted and machined with an aim to achieve high dimensional accuracy and acquire specific performance. However, manufacturing uncertainties result in dimensional deviations causing incompatible operational performance and assembly errors. Process capability limitations of the manufacturer can cause an increase in part rejections, resulting in high production cost. This paper presents a study on a centrifugal impeller with focus on the conceptual design phase to obtain a turbomachine that is robust to manufacturing uncertainties. The impeller has been parameterized and evaluated using a commercial computational fluid dynamics (CFD) solver. Considering the computational cost of CFD, a surrogate model has been prepared for the impeller by response surface methodology (RSM) using space-filling Latin hypercube designs. A sensitivity analysis has been performed initially to identify the critical geometric parameters which influence the performance mainly. Sensitivity analysis is followed by the uncertainty propagation and quantification using the surrogate model based Monte Carlo simulation. Finally a robust design optimization has been carried out using a stochastic optimization algorithm leading to a robust impeller design for which the performance is relatively insensitive to variability in geometry without reducing the sources of inherent variation i.e. the manufacturing noise.

关键词： Compressor impellers Uncertainty Simulation Manufacturing Turbomachinery Conceptual design optimization Turbochargers Noise (Sound) Design optimization algorithms Errors Sensitivity analysis Impellers Geometry Response surface methodology Robustness Computational fluid dynamics

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Improving 3D-Floorplanning Using Smart Selection Operations in Meta-Heuristic optimization

Improving 3D-Floorplanning Using Smart Selection Operations ...

引用

IEEE International 3D Systems Integration Conference (3DIC)

作者： Quiring, Artur Olbrich, Markus Barke, Erich Leibniz Univ Hannover Inst Microelect Syst D-30167 Hannover Germany

ISBN: (纸本)9781467364843

In 3D-Floorplanning even more than in 2D-Floorplanning new objectives, e.g. temperature, TSV-Planning or IR-Drop are considered. This increases the complexity of the problem formulation and, therefore, of the optimization algorithm, dramatically. Apart from some analytical approaches, simulated annealing based algorithms (SA) are widely used for 3D-Floorplanning. To increase the solution quality of classical SA, a common approach is to adapt the selection operations, improving local search. While previous work proposes selection operations which consider mostly one single design issue (e.g. temperature or fixed-outline), we propose a comprehensive multiobjective floorplan optimization methodology (smart SA) which is capable of efficiently considering several objectives and constraints (area, wirelength, fixed-outline, maximum number of TSVs and maximum temperature) at the same time. For the objectives and constraints we present simplified analysis models. Experimental results show that our extended SA algorithm outperforms the classical one and finds valid solutions where classical SA fails.

关键词： Problem Formulation Surgery optimization algorithms Temperature circuit layout

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Poster Abstract: Physical Stigmergy for Decentralized Constrained optimization: An Intelligent Lighting Example

Poster Abstract: Physical Stigmergy for Decentralized Constr...

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4th IEEE/ACM International Conference on Cyber-Physical Systems (ICCPS)

作者： Pavlic, Theodore P. Arizona State Univ Sch Life Sci Tempe AZ 85283 USA

""Conventional distributed solutions for optimization problems with inseparable constraints require significant coordination between agents. Here, a novel numerical approach is described that achieves coordi... 详细信息

ISBN: (纸本)9781450319966

关键词： Bioinspiration Agents and autonomous systems Distributed decentralized control optimization algorithms

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Bayesian optimization Algorithm with Random Immigration

Bayesian Optimization Algorithm with Random Immigration

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1st BRICS Countries Congress on Computational Intelligence / 11th Brazilian Congress on Computational Intelligence (BRICS-CCI and CBIC)

作者： Pucci, Erik Alexandre Ramirez Pozo, Aurora Trinidad Spinosa, Eduardo J. Fed Univ Parana UFPR Dept Informat Curitiba Parana Brazil

ISBN: (纸本)9781479931941

Estimation of Distribution algorithms (EDA) are stochastic population based search algorithms that use a distribution model of the population to create new candidate solutions. One problem that directly affects the EDAs' ability to find the best solutions is the premature convergence to some local optimum due to diversity loss. Inspired by the Random Immigrants technique, this paper presents the Bayesian optimization Algorithm with Random Immigration (BOARI). The algorithm generates and migrates random individuals as a way to improve the performance of the Bayesian optimization Algorithm (BOA) by maintaining the genetic diversity of the population along the generations. The proposed approach has been evaluated and compared to BOA using benchmark functions. Results indicate that, with appropriate settings, the algorithm is able to achieve better solutions than the standard BOA for these functions.

关键词： Bayes methods Genetic algorithms Heuristic algorithms optimization Sociology Standards Statistics boa boari crossover diversity eda immigration Boa Immigration Sociology Heuristic algorithms Bayes methods optimization algorithms Genetic Algorithm (GA) Genetic Crossing Over Bayesian inference

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Adaptive Pattern Nulling Design of Linear Array Antenna by Phase Perturbations Using Invasive Weed optimization Algorithm

Adaptive Pattern Nulling Design of Linear Array Antenna by P...

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International Conference on Information Science and Technology (ICIST)

作者： Wu, Huaning Liu, Chao Dai, Yufeng Naval Univ Engn Dept Commun Engn Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9781467351379

In this paper, invasive weed optimization was used to calculate the p hases of adaptive antenna arrays for the purpose of placing null in the interfering direction and placing maximum power pattern in the desired signal direction to the far-field pattern. IWO algorithm will be stated and computed for this problem. The design results obtained with IWO have been shown to comfortably beat those obtained with PSO.

关键词： linear antenna arrays optimization algorithms Invasive Weeds Antenna arrays adaptive antenna arrays return-to-zero parametric subharmonic oscillator placing perturbation

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Size and parameter adjustment of a hybrid hydraulic powertrain using a global multi-objective optimization algorithm

Size and parameter adjustment of a hybrid hydraulic powertra...

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9th IEEE Vehicle Power and Propulsion Conference (VPPC)

作者： Moulik, Bedatri Karbaschian, Mohammad Ali Soeffker, Dirk Univ Duisburg Essen Chair Dynam & Control D-47057 Duisburg Germany

ISBN: (纸本)9781479907205

In this paper a new approach is developed to optimize the engine and hydraulic element size and their corresponding parameters of a hybrid hydraulic powertrain to given or assumed load/driving cycles. A multi objective optimization algorithm in combination with boundary condition regulation is applied in a loop. In addition, a new mixed optimization algorithm is proposed to overcome the problem of power management optimization by obtaining a better spread of solutions. The main contribution of the paper is the optimal selection of the motor and accumulator size thereby ensuring optimal vehicle dynamic and power consumption properties to different accumulator and engine sizes.

关键词： optimization algorithms parameter adjustment Powertrain Engines optimal selection accumulator Power consumption Hydrodynamics engine sizing Loops

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Application of Extremal optimization Algorithm to Multi-objective Topology Design of Enterprise Networks

Application of Extremal Optimization Algorithm to Multi-obje...

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2013 International Conference on Computer, Control, Informatics and Its Applications (IC3INA)

作者： Khan, Salman A. Univ Pretoria Dept Comp Sci ZA-0002 Pretoria South Africa

ISBN: (纸本)9781479910786

Extremal optimization (EO) is an optimization technique that has been utilized to efficiently solve many complex optimization problems. One such complex problem is topology design of enterprise networks which involves simultaneous optimization of a number of objectives. Some important objectives are financial cost, network delay, maximum number of hops between communicating nodes in the network, and network reliability. The problem also involves a number of design constraints. This paper proposes an EO algorithm to efficiently solve the topology design problem of enterprise network. The multi-objective aspects of the problem are managed through the incorporation of goal programming method in the EO. A preliminary analysis of the proposed EO is presented, and a comparison is done with simulated annealing algorithm which is a well-established optimization algorithm. A program was developed in C++ for simulating the test conditions. Empirical results show the suitability of EO for the problem. Furthermore, EO produced solutions of better quality when compared with the simulated annealing algorithm.

关键词： enterprise networks optimization algorithms design constraints simulated annealing algorithm design problems extremum values topology Goal programming Humulus

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A Deterministic Annealing Approach to optimization of Zero-delay Source-Channel Codes

A Deterministic Annealing Approach to Optimization of Zero-d...

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IEEE Information Theory Workshop (ITW)

作者： Mehmetoglu, Mustafa S. Akyol, Emrah Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)9781479913213

This paper studies optimization of zero-delay source-channel codes, and specifically the problem of obtaining globally optimal transformations that map between the source space and the channel space, under a given transmission power constraint and for the mean square error distortion. Particularly, we focus on the setting where the decoder has access to side information, whose cost surface is known to be riddled with local minima. Prior work derived the necessary conditions for optimality of the encoder and decoder mappings, along with a greedy optimization algorithm that imposes these conditions iteratively, in conjunction with the heuristic "noisy channel relaxation" method to mitigate poor local minima. While noisy channel relaxation is arguably effective in simple settings, it fails to provide accurate global optimization results in more complicated settings including the decoder with side information as considered in this paper. We propose a global optimization algorithm based on the ideas of "deterministic annealing"- a non-convex optimization method, derived from information theoretic principles with analogies to statistical physics, and successfully employed in several problems including clustering, vector quantization and regression. We present comparative numerical results that show strict superiority of the proposed algorithm over greedy optimization methods as well as over the noisy channel relaxation.

关键词： decoders channel spacing optimization algorithms noisy channel deterministic annealing optimization method Codes power transmission Vector quantization side information greedy method ENCODER Global optimization optimality

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