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检索条件"主题词=Optimization Algorithms"

共 4006 条记录，以下是3201-3210 订阅

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Man versus Machine: a Lens Design Challenge

Man versus Machine: a Lens Design Challenge

引用

Conference on Current Developments in Lens Design and Optical Engineering XIV

作者： Dilworth, Donald C. Shafer, David Optical Systems Design Inc. (United States) David Shafer Optical Design (United States)

After a generation of writing and improving lens design software, it is time to assess where we are. Specifically, can a modern program compete with, or surpass, the best human designers? Here we describe a friendly c... 详细信息

ISBN: (纸本)9780819496911

关键词： Lens design global optimization optimization algorithms aberration theory

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Minimization of Cloud Task Execution Length with Workload Prediction Errors

Minimization of Cloud Task Execution Length with Workload Pr...

引用

20th International Conference on High Performance Computing (HiPC)

作者： Di, Sheng Wang, Cho-Li INRIA Paris France Univ Hong Kong Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781479907298

In cloud systems, it is non-trivial to optimize task's execution performance under user's affordable budget, especially with possible workload prediction errors. Based on an optimal algorithm that can minimize cloud task's execution length with predicted workload and budget, we theoretically derive the upper bound of the task execution length by taking into account the possible workload prediction errors. With such a state-of-the-art bound, the worst-case performance of a task execution with a certain workload prediction errors is predictable. On the other hand, we build a close-to-practice cloud prototype over a real cluster environment deployed with 56 virtual machines, and evaluate our solution with different resource contention degrees. Experiments show that task execution lengths under our solution with estimates of worstcase performance are close to their theoretical ideal values, in both non-competitive situation with adequate resources and the competitive situation with a certain limited available resources. We also observe a fair treatment on the resource allocation among all tasks.

关键词： Task execution Error of prediction Workload Budgets Resource utilization CLOUDS Clouds Religious Missions optimization algorithms

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optimization algorithms

Optimization algorithms

引用

International Symposium on Logistics and Industrial Informatics

作者： Csiszar, Sandor Budapest Tech Kalman Kando Fac Elect Engn Inst Microelect & Technol H-1084 Budapest Hungary

ISBN: (纸本)9781424414406

Nowadays an increasing number of papers appears in the subject of combinatorial optimization proposing a great variety of heuristics and metaheuristics, most of them apply special solution to fit the particular problem type. The analysis points out the importance of the generalization but the special intelligence in the algorithm design is still very important. Although the navigation in the solution space can be realized implicitly it has a decisive role in the performance. It is important to note that the success of sophisticated methods is often reduced by their relatively bad explorative capability. The well known algorithms are compared and also the latest most successful methods based on fast and simple heuristics- are discussed.

关键词： Algorithm design Solution space optimization algorithms Heuristics navigation role performance Generalization Fasting Intelligence

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Mixed optimization for Smooth Functions 13

Mixed Optimization for Smooth Functions

引用

Annual Conference on Neural Information Processing Systems

作者： Mehrdad Mahdavi Lijun Zhang Rong Jin Department of Computer Science and Engineering Michigan State University MI USA

ISBN: (纸本)9781632660244

It is well known that the optimal convergence rate for stochastic optimization of smooth functions is O(1/T~(1/2)), which is same as stochastic optimization of Lips-chitz continuous convex functions. This is in contrast to optimizing smooth functions using full gradients, which yields a convergence rate of O(1/T~2). In this work, we consider a new setup for optimizing smooth functions, termed as Mixed optimization, which allows to access both a stochastic oracle and a full gradient oracle. Our goal is to significantly improve the convergence rate of stochastic optimization of smooth functions by having an additional small number of accesses to the full gradient oracle. We show that, with an O(ln T) calls to the full gradient oracle and an O(T) calls to the stochastic oracle, the proposed mixed optimization algorithm is able to achieve an optimization error of O(1/T).

关键词： Smooth function Information retrieval systems-Teletext and videotex Stochastic Function optimization algorithms output transformer Converge Access

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MULTI-OBJECTIVE optimization FOR BRIDGE RETROFIT TO ADDRESS EARTHQUAKE HAZARDS 13

MULTI-OBJECTIVE OPTIMIZATION FOR BRIDGE RETROFIT TO ADDRESS ...

引用

Simulation Conference

作者： Nathanael J. K. Brown Jared L. Gearhart Dean A. Jones Linda K. Nozick Natalia Romero Ningxiong Xu Sandia National Laboratories Albuquerque NM Cornell University Ithaca NY

ISBN: (纸本)9781479920778

Protecting infrastructures against natural hazards is a pressing national and international problem. Given the current budgetary climate, the ability to determine the best mitigation strategies with highly constrained budgets is essential. This papers describes a set of computationally efficient techniques to determine optimal infrastructure investment strategies, given multiple user objectives, that are consistent with an underlying earthquake hazard. These techniques include: optimization methods for developing representative events to characterize the hazard and the post-event condition of infrastructure components, a simulation model to characterize post-event infrastructure performance relative to multiple user objectives, and a multi-objective optimization algorithm for determining protection strategies. They are demonstrated using a case study of the highway network in Memphis, Tennessee.

关键词： road network Refitting detonation hazard Hazards bridges INFRASTRUCTURE Natural Disasters optimization methods optimization algorithms Simulation models infrastructure investments

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Search optimization Algorithm for Satellite Moving Interference Location

Search Optimization Algorithm for Satellite Moving Interfere...

引用

International Congress on Image and Signal Processing

作者： Hongwei Li Jianfeng Chen Xuejun Ji The 54th Research Institute of CETC Shijiazhuang China

ISBN: (纸本)9781479927654

In order to solve the problem of satellite moving interference location, a localization algorithm based on search optimization for dual satellite systems is presented. By using the measurements of the TDOA/FDOA and the Doppler frequency of the moving interfering transmitter, the position of the moving interference can be located in the point of intersection of the curved surface of TDOA/FDOA and the Doppler frequency theoretically. Simulation results verify the effectiveness of the proposed algorithm.

关键词： satellite moving interference location TDOA FDOA Doppler frequency Doppler frequency Moving Satellite systems satellites optimization algorithms

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Bayesian optimization explains human active search 13

Bayesian optimization explains human active search

引用

Annual Conference on Neural Information Processing Systems

作者： Ali Borji Laurent Itti Department of Computer Science USC Los Angeles 90089 Departments of Neuroscience and Computer Science USC Los Angeles 90089

ISBN: (纸本)9781632660244

Many real-world problems have complicated objective functions. To optimize such functions, humans utilize sophisticated sequential decision-making strategies. Many optimization algorithms have also been developed for this same purpose, but how do they compare to humans in terms of both performance and behavior? We try to unravel the general underlying algorithm people may be using while searching for the maximum of an invisible 1D function. Subjects click on a blank screen and are shown the ordinate of the function at each clicked abscissa location. Their task is to find the function's maximum in as few clicks as possible. Subjects win if they get close enough to the maximum location. Analysis over 23 non-maths undergraduates, optimizing 25 functions from different families, shows that humans outperform 24 well-known optimization algorithms. Bayesian optimization based on Gaussian Processes, which exploits all the x values tried and all the f(x) values obtained so far to pick the next x, predicts human performance and searched locations better. In 6 follow-up controlled experiments over 76 subjects, covering interpolation, extrapolation, and optimization tasks, we further confirm that Gaussian Processes provide a general and unified theoretical account to explain passive and active function learning and search in humans.

关键词： Gaussian processes Human Function optimization algorithms Ordinate HUMAN PERFORMANCE Bayesian inference Location analysis

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Computation Time Analysis of a Distributed optimization Algorithm Applied to Automated Irrigation Networks

Computation Time Analysis of a Distributed Optimization Algo...

引用

IEEE Annual Conference on Decision and Control

作者： Alireza Farhadi Michael Cantoni Peter M. Dower Department of Electrical Engineering Sharif University of Technology Tehran Iran Department of Electrical and Electronic Engineering University of Melbourne Victoria Australia

ISBN: (纸本)9781467357159

This paper considers the computation time of two algorithms for solving a structured constrained linear optimal control problem with finite horizon quadratic cost within the context of automated irrigation networks. The first is a standard centralized algorithm based on the interior point method that does not exploit problem structure. The second is distributed and based on a consensus algorithm, not specifically tailored to account for system structure, but devised rather to facilitate the management of conflicting computational and communication overheads. It is shown that there is a significant advantage in terms of computation time in using the second algorithm in large-scale networks. Specifically, for a fixed horizon length the computation time of the centralized algorithm grows as O(n~4) with the number n of sub-systems. By contrast, it is observed via a combination of analysis and experiment that the computation time of the distributed algorithm grows as O(n) with the number n of sub-systems.

关键词： computational time irrigation networks optimization algorithms Irrigation systems interior point method distributed algorithms SUB-SYSTEM Automation

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Hierarchical optimization and Control of a Distribution System

Hierarchical Optimization and Control of a Distribution Syst...

引用

North American Power Symposium

作者： T. Alquthami A. P. Meliopoulos School of Electrical and Computer Engineering Georgia Institute of Technology

ISBN: (纸本)9781479912537

A massive number of distributed energy resources (DER), battery energy storage systems (BESS), and smart appliances (loads) is expected to be deployed in the future. To capture the benefits associated with these emerging units, this paper proposes an advanced infrastructure that allows for an accurate and fast monitoring of the distribution electric feeder including various types of residential, commercial, and industrial loads. This scheme allows for optimizing the utilization and operation of the power system over a short term planning period. More precisely, the concept of distributed optimization algorithm through decomposing the problem into small parts is used to achieve the outlined goals. The enabling technologies that facilitate the implementation of the proposed infrastructure are the advanced metering devices and the distributed state estimation (DSE). The meters, basically, gather the system synchronized and non-synchronized data and send them to the DSE, which evaluates the real time model of the system 60 times per seconds. The results of the DSE are used to perform the optimization and set the controls for the system autonomously.

关键词： dispensing system DSE gene Hydrologic models optimization algorithms Standing Orders Small parts power systems INFRASTRUCTURE

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Consensus for Agents with General Dynamics Using Optimistic optimization

Consensus for Agents with General Dynamics Using Optimistic ...

引用

IEEE Annual Conference on Decision and Control

作者： Lucian Busoniu Irinel-Constantin Morarescu Department of Automation Technical University of Cluj-Napoca Romania Universite de Lorraine CRAN UMR 7039 and CNRS CRAN UMR 7039 2 Avenue de la Foret de Haye Vandoeuvre-les-Nancy France

ISBN: (纸本)9781467357159

An important challenge in multiagent systems is consensus, in which the agents must agree on certain controlled variables of interest. So far, most consensus algorithms for agents with nonlinear dynamics exploit the specific form of the nonlinearity. Here, we propose an approach that only requires a black-box simulation model of the dynamics, and is therefore applicable to a wide class of nonlinearities. This approach works for agents communicating on a fixed, connected network. It designs a reference behavior with a classical consensus protocol, and then finds control actions that drive the nonlinear agents towards the reference states, using a recent optimistic optimization algorithm. By exploiting the guarantees of optimistic optimization, we prove that the agents achieve practical consensus. A representative example is further analyzed, and simulation results on nonlinear robotic arms are provided.

关键词： Agents reference state nonlinearity dynamics Nonlinear Dynamics optimization algorithms robotic arm CONNECTED NETWORKS

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