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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Libo Song Chang Liu Jun Zhu Haibo Shi Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781538604915

A hybrid distribution estimation algorithm for traveling salesman problem is proposed. Firstly, based on the distributed estimation algorithm, a new effective probability model is proposed to solve the traveling salesman problem. Secondly, in order to speed up the optimization of the algorithm to prevent the algorithm falling into the local optimal, the extreme optimization algorithm is combined to form a hybrid distribution estimation algorithm to improve the effectiveness of the algorithm. Then through the public TSPLIB data set, it is proved that the hybrid distribution estimation algorithm is effective, and the algorithm can solve this kind of problem well. Finally, a new idea is proposed to verify the validity of the traveling salesman problem, and the algorithm is tested by the proposed algorithm. The experimental results show that the proposed hybrid distribution estimation algorithm has a good performance in solving the traveling salesman problem.

关键词： Urban areas Estimation Traveling salesman problems optimization Sociology Statistics Encoding travelling salesman problems Sociology algorithms urban area Allocation Algorithm coding optimization algorithms HYBRID Hybrid electric vehicles

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Convex Feasible Set Algorithm for Constrained Trajectory Smoothing

Convex Feasible Set Algorithm for Constrained Trajectory Smo...

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American Control Conference

作者： Changliu Liu Chung-Yen Lin Yizhou Wang Masayoshi Tomizuka Department of Mechanical Engineering University of California Berkeley 94720 USA Faraday & Future Inc Gardena CA 90248 USA

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.

关键词： smoothing trajectory Non-Convex computational time optimization algorithms algorithms Convexity optimization methods

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Optimal production control of a manufacturing-remanufacturing system with delivery activity

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IFAC-PapersOnLine 2016年第12期49卷 1233-1238页

作者： Sadok, Turki Nidhal, Rezg LGIPM/Université de Lorraine Ile du Saulcy Metz Cedex57045 France

This work considers a manufacturing-remanufacturing system composed of two parallel machines, a manufacturing inventory, a purchase warehouse, a recovery inventory and customers who demand a constant quantity of product. Stochastic fluid model is adopted to describe the system and to take into account machine failure, returned products, remanufacturing products and delivery activity. The objective of this paper is to establish an optimal production control which allows minimizing the sum of inventory, transportation and lost sales costs. Perturbation analysis is applied to the stochastic fluid model to determine the optimal manufacturing inventory level that describes the optimal production control. The trajectories of the manufacturing inventory level are studied and the perturbation analysis estimates are evaluated. The unbiasedness of these estimates is proved and then they are implemented in an optimization algorithm which determines the optimal manufacturing inventory in the presence of returned products and delivery time. © 2016

关键词： Stochastic control systems Manufacture Production control Sales Stochastic models Stochastic systems Inventory levels Optimal manufacturing Optimal production optimization algorithms Parallel machine Perturbation Analysis Remanufacturing system Stochastic fluid models

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Comparison of EMD, MEMD and 2T-EMD by analyzing standard artificial signals and EEG

Comparison of EMD, MEMD and 2T-EMD by analyzing standard art...

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International Joint Conference on Neural Networks

作者： Yao Miao Jianting Cao Saitama Institute of Technology

ISBN: (纸本)9781509061839

EEG (electroencephalography) can be analyzed quantitatively by introducing the EEG energy index in EEG preliminary examination of determination of brain death. EMD (empirical mode decomposition), MEMD (multivariate empirical mode decomposition), and 2T-EMD (turning tangent empirical mode decomposition) can be used to analyze coma and quasi-brain-death patients' EEG energy. In this paper, EMD, MEMD, and 2T-EMD are compared from algorithm principle and experimental aspects in order to obtain the optimal algorithm for supporting determination of brain death, where experiments are carried out based on standard artificial signals and patients' EEG. The analysis results illustrate that 2T-EMD is the optimal algorithm with the relative superior computational performance for both single and multi-channel signals.

关键词： Electroencephalography Brain Death optimization algorithms comatic aberration signals MULTICHANNEL

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In-situ re-calibration of implanted pressure sensors

In-situ re-calibration of implanted pressure sensors

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IEEE Sensors

作者： Dixon Leung Simon Malpas Daniel McCormick David Budgett Auckland Bioengineering Institute University of Auckland Auckland

ISBN: (纸本)9781509010134

Feasibility of the novel utilization of a pressure switch mechanism for re-calibrating drifted implanted pressure sensors in-situ is demonstrated. We have designed and characterized the pressure response of a system, which can quantify the offset of a sensor after it has been implanted. The benchtop device is constructed of a 25 pm thick titanium diaphragm with 10 mm working diameter. An optimization algorithm detected a characteristic change in the pressure response produced by the activation of a pressure switch. The repeatability of detection across three sensors is within ±0.23 mmHg over 8 pressurization cycles.

关键词： pressure sensor calibration implantable intracranial pressure hydrocephalus long term drift Pressure Sensor Device Component Implants and Prostheses pressure respond Intracranial Pressure Hydrocephalus Calibration Sensors optimization algorithms

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Optical Tomography based on a nonlinear model that handles multiple scattering

Optical Tomography based on a nonlinear model that handles m...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Morteza Hasani Shoreh Alexandre Goy JooWon Lim Ulugbek Kamilov Michael Unser Demetri Psaltis Optics Laboratory Ecole Polytechnique Federale de Lausanne (EPFL) Switzerland Mitsubishi Electronic Research Laboratories (MERL) Cambridge MA 02139 USA Biomedical Imaging Group Ecole Polytechnique Federale de Lausanne (EPFL) Switzerland Optics Laboratory Ecole Polytechnique Federale de Lausanne (EPFL Switzerland

ISBN: (纸本)9781509041183

Learning Tomography (LT) is a nonlinear optimization algorithm for computationally imaging three-dimensional (3D) distribution of the refractive index in semi-transparent samples. Since the energy function in LT is generally non-convex, the solution it obtains is not guaranteed to be globally optimal. In this paper, we describe linear and nonlinear tomographic reconstruction methods and compare them numerically. We present a review of the LT and, in addition, we investigate the influence of the initialization and exemplify the effect of regularization on the convergence of the algorithm. In particular, we show that both are essential for high-quality imaging in strongly scattering scenarios.

关键词： Optical tomography digital holography multiple scattering computational imaging nonlinear optimization Optical Tomography digital holography MULTIPLE SCATTERING Level Trigger Nonlinear Models optimization algorithms Reconstruction algorithm Handles initialization broadcasting Scattering

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Energy-Efficient Operation of an Indirect Adiabatic Cooling System for Data Centers

Energy-Efficient Operation of an Indirect Adiabatic Cooling ...

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American Control Conference

作者： Alessandro Beghi Giuseppe Dalla Mana Michele Lionello Mirco Rampazzo Enrico Sisti Department of Information Engineering University of Padova via Gradenigo 6/B I-35131 Padova Italy Vertiv Via Leonardo da Vinci 16/18 I-35028 Piove di Sacco Italy Everest s.r.l. via Roveredo 20 I-33170 Pordenone Italy

ISBN: (纸本)9781509045839

Nowadays, the total power consumed by data centers is increasing more and more. In particular, the power consumed by data center facilities accounts for about half of total input power. In this paper, a hierarchical control structure is proposed for efficient management of an indirect adiabatic cooling system, which utilizes fresh air. Data center cooling needs can be met with various combinations of modes of operation that can be set by a supervisor to maximize the overall operating efficiency. Here, the best combination is determined by solving an energy based optimization problem, which is faced by means of a nature-inspired optimization algorithm. The effectiveness of the proposed control system is evaluated by resorting to a simulation environment, that is developed in Matlab/Simulink and where the performance of the computers room air conditioning unit is described.

关键词： total power consumed data center Energy sources power Power Adiabatic cooling Simulated Environment control systems Power (Psychology) Power Surgery Supervisors optimization algorithms Energy efficiency

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Hierarchical Control of a Wind Farm for Wake Interaction Minimization

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IFAC-PapersOnLine 2016年第27期49卷 330-335页

作者： Gionfra, Nicolò Siguerdidjane, Houria Sandou, Guillaume Faille, Damien 3 rue Joliot Curie Gif-sur-Yvette91192 France EDF R&D Department STEP 6 quai Watier Chatou78401 France

The problem of controlling a wind farm for power optimization by minimizing the wake interaction among wind turbines is addressed. We aim to evaluate the real gain in farm power production when the dynamics of the controlled turbines are taken into account. The proposed local control enables the turbines to track the required power references in the whole operating envelope. Simulations are carried out based on a wind farm of 600 kW turbines and they show the actual benefit of considering the wake effect in the optimization algorithm. © 2016

关键词： Electric power system interconnection Electric utilities Feedback linearization Wakes Wind power Wind turbines Hierarchical control optimization algorithms Power optimization Power tracking Predictive control Wake effect Wake interactions Wind farm

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Sparse waveform design for all-spectrum channelization

Sparse waveform design for all-spectrum channelization

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： George Sklivanitis Panos P. Markopoulos Stella N. Batalama Dimitris A. Pados Dept. of Electrical Engineering State University of New York at Buffalo 14260 United States of America Dept. of Electrical and Microelectronic Engineering Rochester Institute of Technology NY 14623 United States of America

ISBN: (纸本)9781509041183

We introduce maximum-SINR sparse-binary waveforms that modulate data information symbols from any finite alphabet and span the whole continuum of the available/device-accessible spectrum. We offer an optimal algorithm that designs the proposed waveforms by maximizing the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum-SINR linear receiver. In addition, we offer a suboptimal algorithm for the same problem with significantly reduced computational complexity. The post-filtering SINR improvements attained by the proposed waveforms in a single-input single-output (SISO) communication system with colored interference are presented analytically. Simulation studies compare the proposed waveforms with their conventional non-sparse counterparts and demonstrate their superior SINR performance.

关键词： All-spectrum binary code sequences maximum SINR sparsity waveform design waveforms SINR Traffic channelization optimization algorithms LINEAR RECEIVERS

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Reordering Buffers with Logarithmic Diameter Dependency for Trees 17

Reordering Buffers with Logarithmic Diameter Dependency for ...

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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete algorithms

作者： Matthias Englert Harald Racke Department of Computer Science and Centre for Discrete Mathematics and its Applications (DIMAP) University of Warwick Department of Informatics Technical University Munich

ISBN: (纸本)9781510836358

In the reordering buffer problem a sequence of items located in a metric space arrive online, and have to be processed by a single server moving within the metric space. At any point in time, the first k still unprocessed items from the sequence are available for processing and the server has to select one of these items and process it by visiting its location. The goal is to process all items while minimizing the total distance the server moves. Englert, Racke, Westermann (STOC'07) gave a deterministic O(D·log k)-competitive online algorithm for weighted tree metrics with hop-diameter D. We improve the analysis of this algorithm and significantly improve the dependency on D. Specifically, we show that the algorithm is in fact O(log D+log k)-competitive. Our analysis is quite robust. Even when an optimal algorithm, to which we compare the online algorithm, is allowed to choose between the first h > k unprocessed items, the online algorithm is still O(h·(log D+log h)/k)-competitive. For h = (1 + ε)·k, with constant ε > 0, this is optimal. Our results also imply better competitive ratio for general metric spaces, improving the randomized O(log n · log~2 k) result for n-point metric spaces from STOC'07 to O(log n·log k).

关键词： metric space Servers algorithms optimization algorithms DEPENDENCE analysis of algorithm Logarithmic

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