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ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS 2018年第39期 23-30页

作者： Das, Raja Reddy, Madhu Sudan VIT Univ Vellore Tamil Nadu India

In this paper, a recurrent neural network (RNN) for finding the solution of linear programming problems is presented with better, spontaneous and fast converging. To achieve optimality in accuracy and also in computational effort, an algorithm is also presented. This paper covers the MATLAB Simulink modeling and simulative confirmation of such a recurrent neural network. Modeling and simulative results validate the theoretical analysis and efficiency of the recurrent neural network for finding the solution for linear programming problem. An application RNN in medicine has been presented to show the performance of the recurrent neural network.

关键词： linear programming problem Recurrent Neural Network (RRN) MATLAB Simulink

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High-performance hybrid genetic algorithm to solve transmission network expansion planning

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第5期11卷 1111-1118页

作者： Gallego, Luis A. Garces, Lina P. Rahmani, Mohsen Romero, Ruben A. Univ Estadual Londrina Dept Elect Engn Londrina Brazil Univ Fed Goias Elect Mech & Comp Engn Sch Goiania Go Brazil Carnegie Mellon Univ Engn & Publ Policy Dept Pittsburgh PA 15213 USA Univ Estadual Paulista Dept Elect Engn Ilha Solteira Brazil

In this study, a high-performance hybrid genetic algorithm (HGA) is proposed to solve static and multistage transmission network expansion planning (TNEP) problem. The main features of the HGA are: (i) it avoids homogenised solutions by using a special genetic algorithm as the backbone of the procedure, (ii) uses a powerful path-relinking algorithm for the deep exploration of local solutions, (iii) employs an efficient constructive heuristic algorithm for finding high-quality initial solutions and for improving solution qualities and (iv) uses a fast relaxation strategy for solving the linear programming problems required for calculating the fitness functions. This procedure will result in an intelligent exploration of a large search space in less amount of time. The proposed methodology is tested with three electrical systems: South Brazilian 46-bus, Colombian 93-bus and the North-Northeast Brazilian 87-bus.

关键词： power transmission planning genetic algorithms linear programming high-performance hybrid genetic algorithm transmission network expansion planning static transmission network expansion planning problem multistage TNEP problem high-performance HGA path-relinking algorithm constructive heuristic algorithm fast relaxation strategy linear programming problem fitness function South Brazilian 46-bus electrical system Colombian 93-bus electrical system North-Northeast Brazilian 87-bus electrical system

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Hierarchical Control Strategy for Maximising Power Conversion in Heaving Wave Energy Converters

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IFAC-PapersOnLine 2017年第1期50卷 14711-14716页

作者： Wahyudie, Addy Saeed, Omsalama Jama, Mohammed Electrical Engineering Department United Arab Emirates University F1 Building PO Box 15551 United Arab Emirates

This paper considers hierarchical control strategy (HCS) for maximising power conversion between mechanical and electrical powers in heaving wave energy converters. The maximisation conversion were obtained by designing the optimum reference for the buoy This reference were found by relating the mechanical and electrical models of the power-takeoff (PTO) device. A simple look-up table of the intrinsic resistance constant was obtained as function of wave's significant height and peak frequency. A Robust PID controller was used to track this reference. The PID controller was tuned using complex polynomial stabilisation method to convert the robust performance specification into a set of linear programming problem. The interesting feature of the method is all (not only one) set of PID parameters, which satisfies the robust performance, were found. Finally, the simulation results were presented to verify the control objectives. © 2017

关键词： Wave energy conversion Control engineering Controllers Electric control equipment linear control systems linear programming Power takeoffs Proportional control systems Robust control Table lookup Three term control systems Wave power Complex polynomials Hierarchical control strategies Intrinsic resistance linear programming problem Mechanical and electrical Ocean energy PID controllers Wave energy converters

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Maximum Transportation Throughput of Automated Guided Vehicle System by use of Models of Traffic Capacity and Traffic Capacity Consumption 3

Maximum Transportation Throughput of Automated Guided Vehicl...

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3rd SICE International Symposium on Control Systems (SICE ISCS)

作者： Kumagai, Kenji Sawada, Kenji Shin, Seiichi Univ Electrocommun Dept Mech Engn & Intelligent Syst Tokyo Japan Murata Machinery Ltd Div Res & Dev Yokohama Kanagawa Japan

ISBN: (纸本)9784907764548

This paper obtains a theoretical value of the maximum transportation throughput of Automated Guided Vehicle (AGV) System in a logistics center. To know the maximum transportation throughput is important to design the system since we need to know the feasibility of the design. It is proposed that the method which the problem to obtain the maximum transportation throughput is reduced to a linear programming problem with in this paper. This method must enable to obtain the theoretical values of large systems in shorter period of time than previous methods. We modeled that a rail have a traffic capacity, and AGVs consume the traffic capacity when they run or wait for loading or unloading. Then these relationship is used as constraints of a linear programming problem whose objective is to maximize the transportation throughput.

关键词： AGV maximum transportation throughput linear programming problem

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Power Supply Company purchase’ portfolio optimisation considering electric vehicle charging load forecasting

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The Journal of Engineering 2017年第13期2017卷 2530-2534页

作者： Yahong Li Hui Ren School of Electrical and Electronic Engineering North China Electric Power University Baoding 071003 People's Republic of China

In recent years, a large number of electric vehicles (EVs) were used and the deployment of EVs will lead to an increase in load and load uncertainty, which introduces volume risk in the bilateral contracts. In order to assess and hedge the risk, the EVs charging load model and the Power Supply Company purchase’ portfolio optimisation model are proposed. A linear programming problem for the Power Supply Company purchase’ portfolio optimisation with conditional value at risk (CVaR) have been formulated, and it contains load uncertainty caused by EVs load, price fluctuation, and the expected cost of errors. This study analyses optimal portfolio allocations to different markets, efficient frontier of CVaR, and the influence of different EVs market penetration levels on the portfolio strategy. The analysis results show that risk of the market increases as the EVs market penetration level increases. Power Supply Company may hedge risk through adjusting the optimal portfolio allocation to different electricity markets.

关键词： investment pricing power markets load forecasting linear programming electric vehicle charging load uncertainty portfolio strategy optimal portfolio allocation electric vehicle volume risk load model electricity markets EV load optimal portfolio allocations EV market penetration levels power supply company purchase portfolio optimisation model electric vehicle charging load forecasting linear programming problem CVaR

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A Study on Controlled Node Sized Network Clustering for Unweighted Network Data

A Study on Controlled Node Sized Network Clustering for Unwe...

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International Symposium on Advanced Intelligent Systems

作者： Shusuke Nakano Yukihiro Hamasuna Yasunori Endo Graduate School of Sci. and Eng. Kindai University 3-4-1 Kowakae Higashiosaka Osaka Japan School of Sci. and Eng. Kindai University 3-4-1 Kowakae Higashiosaka Osaka Japan Faculty of Eng. Info. and Sys. University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki Japan

ISBN: (纸本)9781538626344;9781538626337

The Louvain method is one of the typical network clusterings. It is well-known that the Louvain method obtains better cluster partition in a short time. However, there are several network data which are not obtained better cluster partition by the Louvain method. One of the reasons for the above is that the Louvain method focuses on an only edge connection. We proposed the method which focuses on node size. The proposed method optimizes the objective function of k-medoids by solving the linear programming problem under the constraints on node size. We verified the usefulness of the proposed method in the viewpoint of calculation time and accuracy with an artificial and benchmark unweighted network datasets. The numerical examples show that the proposed method is faster and obtains better cluster partition than the Louvain method. The Euclidean distance in adjacency matrix does not obtain better cluster partition for the datasets, which consist of terminal nodes or high degree nodes.

关键词： Network clustering linear programming problem Modularity K-medoids Controlled size

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One class proximal support vector machines

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PATTERN RECOGNITION 2016年 52卷 96-112页

作者： Dufrenois, F. Noyer, J. C. Univ Littoral Cote dOpale Lab Informat Signal & Image Cote Opale BP71950 Rue Ferdinand Buisson F-62228 Calais France

Recently in Dufrenois [1], a new Fisher type contrast measure has been proposed to extract a target population in a dataset contaminated by outliers. Although mathematically sound, this work presents some further shortcomings in both the formalism and the field of use. First, we propose to re-express this problem from the formalism of proximal support vector machines as introduced in Mangasarian and Wild [2]. This change is far from harmless since it introduces a suited writing for solving the problem. Another limiting factor of the method is that its performance relies on the assumption that the density between the target and outliers are different. This consideration can easily prove to be over-optimistic for real world datasets making the method unreliable, at least directly. The computation of the decision boundary is a time consuming part of the algorithm since it is based on solving a generalized eigenvalue problem (GEP). This method is therefore limited to medium sized data sets. In this paper, we propose appropriate strategies to unlock all these shortcomings and fully benefit from the interest of the approach. Firstly, we show under some conditions that generating appropriate artificial outliers allows to stay within the constraints of the method and thus enlarges the conditions of use. Secondly, we show that the GEP can be advantageously replaced by a conjugate gradient solution (CG) significantly decreasing the computational cost. Lastly, the proposed algorithm is compared with recent novelty detectors on synthetic and real datasets. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Outlier detection Proximal support vector machines linear programming problem Contrast measure

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A new method for solving fuzzy linear fractional programming problems

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2016年第3期31卷 1831-1843页

作者： Veeramani, C. Sumathi, M. PSG Coll Technol Dept Appl Math & Computat Sci Coimbatore 641004 Tamil Nadu India PSG Coll Technol Dept Math Coimbatore Tamil Nadu India

Fuzzy linear Fractional programming problem has been used as an important planning tool for the different disciplines such as engineering, business, finance, economics, etc. In this paper, a new algorithm is developed to solve the Fuzzy linear Fractional programming problem (FLFPP) where the cost of the objective function, the resources and the technological coefficients are triangular fuzzy numbers. For this, the FLFPP is transformed into an equivalent deterministic Multi Objective linear Fractional programming problem (MOLFPP) and solved them each objective function. From the obtained solutions, we define an imprecise and aspiration level for each objectives. Hence, the objectives are transformed as fuzzy goal. Then the goal programming approach is used to achieve the highest degree of each of the membership goals by minimizing their deviational variables. Finally, two real examples and one case study problem will be used to illustrate our algorithm and compare it with the existing method.

关键词： Triangular fuzzy number linear programming problem multi objective linear programming problem goal programming

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An alternative approach for compatibility of two discrete conditional distributions

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2016年第15期45卷 4416-4432页

作者： Ghosh, Indranil Nadarajah, Saralees Austin Peay State Univ Dept Math Clarksville TN 37044 USA Univ Manchester Sch Math Manchester Lancs England

Conditional specification of distributions is a developing area with increasing applications. In the finite discrete case, a variety of compatible conditions can be derived. In this paper, we propose an alternative approach to study the compatibility of two conditional probability distributions under the finite discrete setup. A technique based on rank-based criterion is shown to be particularly convenient for identifying compatible distributions corresponding to complete conditional specification including the case with *** proposed methods are illustrated with several examples.

关键词： Compatible conditional distribution linear programming problem Rank-based criterion 62E20

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V-bar and R-bar Glideslope Guidance Algorithms for Fixed-Time Rendezvous: A linear programming Approach

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IFAC-PapersOnLine 2016年第17期49卷 385-390页

作者： Ariba, Yassine Arzelier, Denis Urbina, Laura Sofia Louembet, Christophe ICAM 75 avenue de Grande Bretagne Toulouse31300 France CNRS LAAS Univ de Toulouse 7 avenue du colonel Roche ToulouseF-31400 France CNRS LAAS Univ de Toulouse UPS 7 avenue du colonel Roche ToulouseF-31400 France

This paper presents minimum-fuel glideslope autonomous guidance algorithms for approaching a target evolving on a circular orbit. In the context of a chemical propulsion, the classical multipulse glideslope algorithm of Hablani is revisited and it is shown that when considering specific common directions for the glideslope such as V-bar and R-bar directions, a linear formulation of the circular minimum-fuel linearized rendezvous problem may be deduced. Unlike the classical glideslope algorithm for which there is no direct control on the fuel consumption, additional degrees of freedom and relevant decision variables may be identified by combining an analytical expression for the maximal guidance error and Hill-Clohessy-Wiltshire relative equations of motion. For a fixed-time rendezvous with a pre-assigned number of maneuvers, a fuel-optimal solution with a bounded guidance error is obtained by solving a linear programming problem. Numerical examples demonstrate the usefulness of the approach with respect to the classical ones when the approach corridor has to fulfill stringent geometrical restrictions such as line-of-sight constraints. © 2016

关键词： Air navigation Degrees of freedom (mechanics) Equations of motion Fuels linear programming Analytical expressions Chemical propulsion circular rendezvous Glideslope Hill Clohessy Wiltshire equations Impulsive controls Line of sight constraints linear programming problem

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