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Sensitivity Analysis of Design Parameters in Transverse Flux Induction Heating Device

IEEE TRANSACTIONS ON APPLIED SUPERCONDUCTIVITY 2020年第4期30卷 1-6页

作者： Wu, Jiancheng C., Jr. Wang, Shaopeng P., Jr. Wang, Youhua H. Liu, Chengcheng Hebei Univ Technol State Key Lab Reliabil & Intelligence Elect Equip Tianjin 300130 Peoples R China

In this paper, the Morris method of qualitative global sensitivity analysis (GSA) is used to rank the sensitivity values among four design parameters and three objectives of transverse flux induction heating (TFIH) device. The design parameters include effective value and frequency of the exciting current, the moving speed of the strip and the length of the coil along the width direction of the strip. The objective functions include relative non-uniformity of strip surface temperature distribution along strip width direction at heater outlet, average temperature of strip surface perpendicular to strip movement direction at heater outlet and heating efficiency of TFIH device. Each objective function is calculated by three dimensional (3D) finite element method (FEM). The sensitivity values ranking provides an optimal priority for the optimization or change of the design parameters of TFIH device.

关键词： Design parameters global sensitivity analysis (GSA) Morris method objective functions parameters optimization transverse flux induction heating (TFIH)

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Multi-objective optimisation method for coordinating battery storage systems, photovoltaic inverters and tap changers

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IET RENEWABLE POWER GENERATION 2020年第3期14卷 475-483页

作者： Hashemipour, N. Aghaei, Jamshid Lotfi, Mohamed Niknam, Taher Askarpour, Mohammad Shafie-khah, Miadreza Catalao, Joao P. S. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Univ Porto Fac Engn P-4200465 Porto Portugal INESC TEC P-4200465 Porto Portugal Univ Vaasa Sch Technol & Innovat Vaasa 65200 Finland

The many well-established advantages of distributed generation (DG) make their usage in active distribution networks prevalent. However, uncontrolled operation of DG units can negatively interfere with the performance of other equipment, such as tap-changers, in addition to resulting in sub-optimal usage of their potential. Thus, adequate scheduling/control of DG units is critical for operators of the distribution system to avoid those adverse effects. A linearised model of a multi-objective method for coordinating the operation of photovoltaics, battery storage systems, and tap-changers is proposed. Three objective functions are defined for simultaneously enhancing voltage profile, minimising power losses, and reducing peak load power. The formulated multi-objective problem is solved by means of the epsilon-constraint technique. A novel decision-making methodology is offered to find the Pareto optimality and select the preferred solution. To assess to proposed model's performance, it is tested using 33-bus IEEE test system. Consequently, tap-changers suffer lessened stress, the batteries state-of-charge is kept within adequate limits, and the DG units operation is at higher efficiency. The obtained results verify the effectiveness of this approach.

关键词： optimisation distributed power generation distribution networks Pareto optimisation decision making multiobjective optimisation method battery storage systems photovoltaic inverters tap changers well-established advantages distributed generation active distribution networks uncontrolled operation tap-changers sub-optimal usage distribution system multiobjective method objective functions peak load power formulated multiobjective problem 33-bus IEEE test system batteries state-of-charge DG units operation

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Admission control with incomplete information of a queueing system

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OPERATIONS RESEARCH 2003年第4期51卷 645-654页

作者： Lin, KY Ross, SM Virginia Polytech Inst & State Univ Grado Dept Ind & Syst Engn Blacksburg VA 24061 USA Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA 94720 USA

We consider a multiple-server loss model where customers arrive at a gatekeeper according to a Poisson process. A cost c is incurred if a new arrival is blocked from entering the system by the gatekeeper, while a larger cost K is incurred if an admitted customer finds all servers busy and therefore has to leave the system. The key assumption is that the gatekeeper is informed when an admitted customer finds all servers busy, but is not informed when served customers depart. Assuming an exponential service distribution, we show that, in the case of a single server. a threshold-type policy that blocks for a certain amount of time after a new arrival is admitted is optimal. When there are multiple servers, we propose two types of heuristic policies. We analytically compute the best policy of the first type, and use simulation to estimate that of the other.

关键词： Optimal policy Heuristics Network servers Hyperlinks Optimal control objective functions Average cost functions Average total cost Cost functions

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Revisiting density-based topology optimization for fluid-structure-interaction problems

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2018年第3期58卷 969-995页

作者： Lundgaard, Christian Alexandersen, Joe Zhou, Mingdong Andreasen, Casper Schousboe Sigmund, Ole Tech Univ Denmark Dept Mech Engn Richard Petersens Plads Bldg 322 DK-2800 Lyngby Denmark Shanghai Jiao Tong Univ Shanghai Key Lab Digital Manufacture Thin Walled State Key Lab Mech Syst & Vibrat 800 Dong Chuan Rd Shanghai 200240 Peoples R China

This study revisits the application of density-based topology optimization to fluid-structure-interaction problems. The Navier-Cauchy and Navier-Stokes equations are discretized using the finite element method and solved in a unified formulation. The physical modeling is limited to two dimensions, steady state, the influence of the structural deformations on the fluid flow is assumed negligible, and the structural and fluid properties are assumed constant. The optimization is based on adjoint sensitivity analysis and a robust formulation ensuring length-scale control and 0/1 designs. It is shown, that non-physical free-floating islands of solid elements can be removed by combining different objective functions in a weighted multi-objective formulation. The framework is tested for low and moderate Reynolds numbers on problems similar to previous works in the literature and two new flow mechanism problems. The optimized designs are consistent with respect to benchmark examples and the coupling between the fluid flow, the elastic structure and the optimization problem is clearly captured and illustrated in the optimized designs. The study reveals new features of topology optimization of FSI problems and may provide guidance for future research within the field.

关键词： Topology optimization Fluid-structure-interaction Adjoint sensitivity analysis The robust formulation objective functions Flow mechanisms

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OPTIMAL 2-FACILITY NETWORK DISTRICTING IN THE PRESENCE OF QUEUING

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TRANSPORTATION SCIENCE 1985年第3期19卷 261-277页

作者： BERMAN, O LARSON, RC UNIV CALGARY CALGARY T2N 1N4ALBERTACANADA MIT CAMBRIDGEMA 02139

This paper considers a districting problem for a demand-responsive service system in which queuing is allowed. Customers, located at the nodes of a transportation network, call in a Poisson manner, asking for on-scene service by a mobile service unit. Two such units service the entire network, with unit i(i = 1, 2) responsible for all nodes Nⁱ in its unique “service territory.” In response to a call from within N^?, unit i, if available, is dispatched immediately to the customer; if the unit is busy with a previous customer, the call is dispatched in a FIFO manner. Each service territory, with its response unit, behaves as an independently operating M/G/1 queuing system. The problem addressed in this paper is determination of the optimal service territories, given fixed home locations for each of the service units, so as to minimize the average response time (queuing delay plus travel time) to a random customer. Exact results are obtained for limiting values of demand rate, and efficient heuristics are presented for arbitrary demand rates.

关键词： Heuristics Optimal solutions Optimal policy Travel time Integers objective functions Manners Emergency vehicles Trip length Integrality

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Multi-objective differential evolution-based ensemble method for brain tumour diagnosis

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IET IMAGE PROCESSING 2019年第9期13卷 1421-1430页

作者： Rezaei, Kimia Agahi, Hamed Mahmoodzadeh, Azar Islamic Azad Univ Shiraz Branch Dept Elect Engn Shiraz Iran

Accurate diagnosis of tumour type is a paramount issue in the appropriate treatment of cancer. In this study, a novel multi-step method, recognising benign and malignant tumour slices in real brain computed tomography (CT) images is proposed. First, image reconstruction is conducted for mixed noise removal using 'weighted encoding with sparse non-local regularisation' technique. For the segmentation purpose, support vector machine (SVM) is performed on CT images. Afterwards, 17 features are extracted, among which multiple important features are selected by the genetic algorithm. These selected features are used as the input to the multilayer perceptron neural network, the weighted kernel width SVM and the k-nearest neighbours models in tumour classification phase. Following this, the outcomes of mentioned classifiers are combined by means of multi-objective differential evolution-based ensemble technique, in order to enhance the classification performance indices. The parameters of this weighted linear combination are found by solving an optimisation problem containing precision and recall as the objective functions. The performance of the implemented approach is compared with the experienced radiologist ground truth and some state-of-the-art methods. The results demonstrate that the ensemble technique achieves high classification rates including the accuracy of 98.65%.

关键词： medical image processing brain cancer genetic algorithms image classification image texture feature extraction statistical analysis tumours multilayer perceptrons computerised tomography support vector machines image segmentation image denoising image reconstruction multiobjective differential evolution-based ensemble method brain tumour diagnosis tumour type paramount issue benign tumour slices malignant tumour slices tomography images image reconstruction mixed noise removal weighted encoding nonlocal regularisation technique segmentation purpose support vector machine CT images genetic algorithm multilayer perceptron neural network weighted kernel width SVM nearest neighbours models tumour classification phase classification performance indices weighted linear combination objective functions multistep method

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Common fallacies in estimation and control under uncertainty

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JOURNAL OF PROCESS CONTROL 1996年第5期6卷 295-307页

作者： Agarwal, M TCL Eidgenössische Technische Hochschule CH-8092 Zurich Switzerland

Examples from the literature are used to illustrate certain common fallacies in the development of estimators and controllers under uncertainty. It is shown that the common notions of process, model, objective, and method must carefully be distinguished from one another and from additional concepts of attitude and best strategy. Failure to do so can readily lead to false claims and sub-optimal, or even useless, schemes. Concrete guidelines are provided to avoid the fallacies and to better focus the research effort.

关键词： objective functions optimal methods worst-case design

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On Optimal Clustering in Mobile Wireless Sensor Networks Under Uncertainty

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MILITARY OPERATIONS RESEARCH 2015年第2期20卷 19-33页

作者： Degirmenci, Guvenc Kharoufeh, Jeffrey P. Prokopyev, Oleg A. Univ Pittsburgh Pittsburgh PA 15260 USA

Wireless sensor networks are comprised of geographically distributed sensors that collect and convey time-critical information without human intervention, making them particularly useful for military applications;however, network performance may be limited by the typically small energy supplies of the sensors. One strategy for dealing with limited energy storage in such networks is to allow sensor nodes to aggregate sensed data at particular nodes known as cluster heads. We examine the problem of optimally locating and relocating cluster heads over a finite time horizon. The objective is to simultaneously maximize the demand coverage and minimize the costs of relocating cluster heads. Our main contribution is to consider explicitly the random evolution of mobile sensor nodes, which requires periodic updating of their precise locations. Computational experiments illustrate the usefulness of such dynamic information updates to help mitigate the uncertainty in sensor node locations and ensure reliable demand coverage by cluster heads.

关键词： Sensors Algorithms Operations research Connectivity Military operations objective functions Variable costs Cost functions Heuristics Unit costs

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Modified bio-inspired optimisation algorithm with a centroid decision making approach for solving a multi-objective optimal power flow problem

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第4期11卷 1012-1022页

作者： Barocio, Emilio Regalado, Jose Cuevas, Erick Uribe, Felipe Zuniga, Pavel Ramirez Torres, Pedro J. Univ Guadalajara Grad Program Elect Engn Av Revoluc 1500 Guadalajara Jalisco Mexico Univ Guadalajara Dept Computat Sci Av Revoluc 1500 Guadalajara Jalisco Mexico Imperial Coll London Dept Elect & Elect Engn London England

A method to solve a multi-objective optimal power flow (MOOPF) problem with multiple and competing objective functions (OF) is presented. The modified flower pollination algorithm and the normal boundary intersection method are used in a complementary way to determine the Pareto front solution of the MOOPF problem. To help in the decision making process, an intuitive criterion based on the centroid concept is proposed to select the best compromise solution from the Pareto frontier. To demonstrate the capabilities of the proposed method, different OFs are combined to calculate the Pareto front solution on the IEEE 30 bus test system. Finally, a comparison of the proposed centroid based method against the well-known fuzzy membership and entropy criterions is provided in the results section.

关键词： decision making optimisation load flow modified bio-inspired optimisation algorithm centroid decision making approach multiobjective optimal power flow problem modified flower pollination algorithm objective functions normal boundary intersection method Pareto front solution MOOPF problem IEEE 30 bus test system Pareto frontier fuzzy membership entropy criterions

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DUALITY IN NONLINEAR PROGRAMMING - SIMPLIFIED APPLICATIONS-ORIENTED DEVELOPMENT

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SIAM REVIEW 1971年第1期13卷 1-+页

作者： GEOFFRION, AM

The number of computational or theoretical applications of nonlinear duality theory is small compared to the number of theoretical papers on this subject over the last decade. This study attempts to rework and extend the fundamental results of convex duality theory so as to diminish the existing obstacles to successful application. New results are also given having to do with important but usually neglected questions concerning the computational solution of a program via its dual. Several applications are made to the general theory of convex systems.

关键词： Optimal solutions Mathematical duality Convexity Mathematical functions Scalars Value theorems Tangents objective functions

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