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Joint optimal resource allocation schemes for downlink cooperative cellular networks over orthogonal frequency division multiplexing carriers

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IET COMMUNICATIONS 2020年第10期14卷 1560-1570页

作者： Kaveh, Fatemeh Soleimanpour, Mohadese Talebi, Siamak Shahid Bahonar Univ Kerman Dept Elect Engn Kerman Iran Higher Educ Complex Bam Dept Mech Engn Bam Iran

This study concentrates on the study of a downlink cooperative cellular (DCC) network in which an access point is located in the centre of each cell and two relay stations are installed in the border between both sectors of a cell to obtain higher cell-edge throughput. To optimise the network efficiency, a joint optimal subcarrier and power allocation scheme is proposed which initially derives the highest achievable rate for a single-legacy user (LU), then, through further evaluation and analysis, this is generalised to the case of a multiple-LU environment. Next, to maximise the overall throughput and ensure fairness, a multi-objective lexicographical optimisation problem (MLOP) is formulated to maximise the minimum LUs rate while improving the overall throughput. As the proposed MLOP is a mixed-integer non-linear problem, finding optimal solutions is impractical and in general, there is no standard method for optimally obtaining a solution. Hence, two efficient algorithms are introduced in this study. Simulation results confirm that the proposed algorithms achieve a fair and near-optimal performance for the multi-LU DCC network based on two relay channels, which makes them desirable in practice compared to some of the sub-optimal well-known algorithms investigated in this study.

关键词： OFDM modulation resource allocation integer programming linear programming minimax techniques cellular radio nonlinear programming near-optimal performance multiLU DCC network relay channels joint optimal resource allocation schemes downlink cooperative cellular network access point relay stations cell-edge throughput network efficiency joint optimal subcarrier power allocation scheme highest achievable rate single-legacy user multiple-LU environment multiobjective lexicographical optimisation problem MLOP minimum LUs rate mixed-integer nonlinear problem fair performance

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QuateRA: The Quaternion Regression Algorithm

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2020年第9期43卷 1600-1616页

作者： de Almeida, Marcelino M. Mortari, Daniele Zanetti, Renato Akella, Maruthi Univ Texas Austin Dept Aerosp Engn & Engn Mech Austin TX 78712 USA Texas A&M Univ Dept Aerosp Engn College Stn TX 77843 USA Univ Texas Austin Aerosp Engn & Engn Mech Austin TX 78712 USA

This work proposes a batch solution to the problem of estimating fixed angular velocity using orientation measurements. Provided that the angular velocity remains constant with time, it is shown that the orientation quaternion belongs to a constant plane of rotation as time evolves. Motivated by this fundamental property, the angular velocity's direction can be determined by estimating the quaternion plane of rotation. Under the small angle assumption on the attitude measurement noise, the plane of rotation is estimated by minimizing a constrained total least-squares cost function, and the proposed algorithm produces a unique optimizing solution through a batch approach (no need for iterations). The angular velocity magnitude is estimated by projecting the measured quaternions onto the estimated plane of rotation, and then computing the least-squares evolution of the quaternion angle in the plane. A Monte Carlo analysis of the proposed algorithm is performed, validating the method and comparing it with a multiplicative extended Kalman Filter, which is a traditional method in the literature.

关键词： Singular Value Decomposition Extended Kalman Filter Monte Carlo Simulation Computing Attitude Dynamics Taylor Series nonlinear programming Rotational Kinematics Attitude Kinematics Gyroscopes

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Optimal offshore wind farms connection considering the wind capacity maximisation - a Benders decomposition approach

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IET RENEWABLE POWER GENERATION 2020年第10期14卷 1772-1781页

作者： Vasconcelos, Leandro Almeida Passos Filho, Joao Alberto de Oliveira, Leonardo Willer Fed Univ Juiz de Fora UFJF Dept Elect Engn Jose Lourenco Kelmer St S-N Juiz De Fora MG Brazil Fed Inst Northern Minas Gerais IFNMG Dept Elect Engn Dois St 300 Village Lago 1 BR-39404058 Montes Claros MG Brazil

This study presents a new methodology to determine the optimal Offshore Wind Farms connection point in a power system, with the purpose of maximising the wind power penetration, considering a Benders decomposition approach to represent the security constraints related to the 'N - 1' contingency criterion. The proposed algorithm uses a mixed-integer non-linear programming approach associated with a non-linear programming, and it is evaluated in a tutorial system (IEEE 14-Bus) and two networks from the literature: a small case (IEEE RTS-79), and a medium and real case (Brazilian Birds System). In each case, three points geographically close to each other are selected as candidates in the onshore grid for the wind power injection. The experiments conducted clearly show that the connection decision from the proposed approach led to the maximum safe wind power penetration among the candidate options, which proves its applicability and effectiveness, even for more complex networks, and considering all single transmission line contingencies for safe operation.

关键词： nonlinear programming power system security wind power offshore installations wind power plants integer programming power generation reliability Benders decomposition approach power system security constraints mixed-integer nonlinear programming approach tutorial system IEEE 14-Bus IEEE RTS-79 Brazilian Birds System wind power injection connection decision maximum safe wind power penetration wind capacity maximisation optimal offshore wind farms connection point contingency criterion single transmission line contingencies safe operation

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Placement optimisation for station-free bicycle-sharing under 1D distribution assumption

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IET INTELLIGENT TRANSPORT SYSTEMS 2020年第9期14卷 1079-1086页

作者： Wang, Shuofeng Li, Zhiheng Gu, Ruochen Xie, Na Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Tsinghua Univ Grad Sch Shenzhen Shenzhen 518055 Peoples R China Natl Inst Metrol Informat & Elect Div Beijing 100013 Peoples R China Cent Univ Finance & Econ Sch Management Sci & Engn Beijing 100081 Peoples R China

Bicycles become popular again in the transportation system because they could serve as useful tools for convenient, economical, and environmentally friendly short-trips. In the traditional public bicycle system, customers need to reach a fixed public bicycle station before they can rent a public bicycle. However, the current station-free bicycle-sharing systems can allow customers to borrow or return shared bicycles, which would be distributed almost anywhere. Such new systems bring new optimisation problems for bicycle management. The authors study a placement optimisation problem that highlights the distribution characteristics of shared bicycles, aiming to minimise the total walking distance of customers. The proposed model is a 0-1 mix-integer non-linear programme. To solve the model, they propose a bi-level solving framework. The upper-level model optimises the locations of supply stations. The lower-level model optimises the number of bikes assigned to each demand site. A test based on the campus of Tsinghua University is employed to validate the proposed model. The optimal location suggested by their model is significantly different from the location suggested by models that ignore the distributed feature. Their model performs better in terms of reducing the total walking distance.

关键词： nonlinear programming bicycles transportation integer programming 1D distribution assumption transportation system environmentally friendly short-trips fixed public bicycle station shared bicycles bicycle management placement optimisation problem total walking distance 0-1 mix-integer nonlinear programme supply stations distributed feature optimal location

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IMPLEMENTING A SMOOTH EXACT PENALTY FUNCTION FOR GENERAL CONSTRAINED nonlinear OPTIMIZATION

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 2020年第3期42卷 A1836-A1859页

作者： Estrin, Ron Friedlander, Michael P. Orban, Dominique Saunders, Michael A. Stanford Univ Inst Computat & Math Engn Stanford CA 94305 USA Univ British Columbia Dept Comp Sci Vancouver BC V6T 1Z4 Canada Ecole Polytech GERAD Montreal PQ Canada Ecole Polytech Dept Math & Ind Engn Montreal PQ Canada Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA

We build upon R. Estrin et al., [SIAM J. Sci. Comput., 42 (2020), pp. A1809-A1835] to develop a general constrained nonlinear optimization algorithm based on a smooth penalty function proposed by R. Fletcher [Integer and nonlinear programming, J. Abadie, ed., North-Holland, Amsterdam, (1970), pp. 157-175;Math. Program., 5 (1973), pp. 129-150]. Although Fletcher's approach has historically been considered impractical, we show that the computational kernels required are no more expensive than those in other widely accepted methods for nonlinear optimization. The main kernel for evaluating the penalty function and its derivatives solves structured linear systems. When the matrices are available explicitly, we store a single factorization each iteration. Otherwise, we obtain a factorization-free optimization algorithm by solving each linear system iteratively. The penalty function shows promise in cases where the linear systems can be solved efficiently, e.g., PDE-constrained optimization problems when efficient preconditioners exist. We demonstrate the merits of the approach, and give numerical results on several PDE-constrained and standard test problems.

关键词： nonlinear programming exact penalty smooth penalty factorization free iterative methods trust region

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Tight convex relaxation for TEP problem: a multiparametric disaggregation approach

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第14期14卷 2810-2817页

作者： Goodarzi, Shahin Gitizadeh, Mohsen Abbasi, Ali Reza Lehtonen, Matti Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Fasa Univ Dept Elect & Elect Engn Fasa Iran Alto Univ Dept Elect Engn & Automat Espoo 02150 Finland

In recent years, there has been an increasing interest in using AC power flow equations for the transmission expansion planning (TEP) studies. The AC power flow equations are quadratic and hence the TEP problem can be formulated as a mixed-integer quadratically constrained programme. Therefore, the complexity of the TEP problem lies in the non-convexity of AC power flow equations in which the global optimal solution is not guaranteed to be found. This study aims at proposing a tight convex relaxation for the TEP problem. In this context, first, the TEP problem is formulated as a mixed-integer bilinear problem by representing the complex bus voltage in its rectangular coordinates. Second, the multiparametric disaggregation technique (MDT) and piecewise McCormick relaxation are employed to generate a mixed-integer linear relaxation. MDT is based on the discretisation of the domain of one of the variables in every bilinear term. The method presented is much more precise compared with the DC or other linearisation approaches, while the optimal solution is of high quality. The results of the case studies show the tractability and exactness of the proposed model as well as its superiority over the state-of-the-art schemes.

关键词： integer programming quadratic programming convex programming linear programming concave programming load flow power transmission planning nonlinear programming tight convex relaxation TEP problem AC power flow equations transmission expansion planning studies mixed-integer bilinear problem mixed-integer linear relaxation

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A restart scheme for the Dai-Liao conjugate gradient method by ignoring a direction of maximum magnification by the search direction matrix

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RAIRO-OPERATIONS RESEARCH 2020年第4期54卷 981-991页

作者： Aminifard, Zohre Babaie-Kafaki, Saman Semnan Univ Dept Math Fac Math Stat & Comp Sci POB 35195-363 Semnan Iran

As known, finding an effective restart procedure for the conjugate gradient methods has been considered as an open problem. Here, we aim to study the problem for the Dai-Liao conjugate gradient method. In this context, based on a singular value analysis conducted on the Dai-Liao search direction matrix, it is shown that when the gradient approximately lies in the direction of the maximum magnification by the matrix, the method may get into some computational errors as well as it may converge hardly. In such situation, ignoring the Dai-Liao search direction in the sense of performing a restart may enhance the numerical stability as well as may accelerate the convergence. Numerical results are reported;they demonstrate effectiveness of the suggested restart procedure in the sense of the Dolan-More performance profile.

关键词： nonlinear programming unconstrained optimization conjugate gradient method restart strategy maximum magnification

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Penalty Force for Coupling Materials with Coulomb Friction

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2020年第7期26卷 2443-2455页

作者： Ding, Ounan Schroeder, Craig Univ Calif Riverside Riverside CA 92521 USA

We propose a novel penalty force to enforce contacts with accurate Coulomb friction. The force is compatible with fully-implicit time integration and the use of optimization-based integration. The contact force is quite general. In addition to processing collisions between deformable objects, the force can be used to couple rigid bodies to deformable objects or the material point method. The force naturally leads to stable stacking without drift over time, even when solvers are not run to convergence. The force leads to an asymmetrical system, and we provide a practical solution for handling these.

关键词： Force Friction Couplings Springs Dynamics Mathematical model Computer graphics Computer graphics animation nonlinear programming

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Complexity and performance of an Augmented Lagrangian algorithm

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OPTIMIZATION METHODS & SOFTWARE 2020年第5期35卷 885-920页

作者： Birgin, E. G. Martinez, J. M. Univ Sao Paulo Inst Math & Stat Dept Comp Sci Rua Matao 1010Cidade Univ BR-05508090 Sao Paulo SP Brazil Univ Estadual Campinas Inst Math Stat & Sci Comp Dept Appl Math Campinas Brazil

Algencan is a well established safeguarded Augmented Lagrangian algorithm introduced in [R. Andreani, E. G. Birgin, J. M. Martinez, and M. L. Schuverdt, On Augmented Lagrangian methods with general lower-level constraints, SIAM J. Optim. 18 (2008), pp. 1286-1309]. Complexity results that report its worst-case behaviour in terms of iterations and evaluations of functions and derivatives that are necessary to obtain suitable stopping criteria are presented in this work. In addition, its computational performance considering all problems from the CUTEst collection is presented, which shows that it is a useful tool for solving large-scale constrained optimization problems.

关键词： nonlinear programming Augmented Lagrangian methods complexity numerical experiments

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A QFD-Based Quality and Capability Design Method for Transboundary Services

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MATHEMATICAL PROBLEMS IN ENGINEERING 2020年第1期2020卷 1-18页

作者： Ma, Chao Liu, Wei Dong Tu, Zhi Ying Wang, Zhong Jie Xu, Xiao Fei Harbin Univ Sci & Technol Sch Software & Microelect Harbin Peoples R China Harbin Inst Technol Sch Comp Sci & Technol Harbin Peoples R China

The "transboundary", an emerging phenomenon in the Internet service ecosystem, is leading to the flourishing of innovative services. A transboundary service incorporates services, resources, and technologies from multiple domains into its business to create a particular competitive advantage and unique user experiences. It is difficult to comprehensively consider all the constraints from multiple domains to precisely design the nonfunctional characteristics of transboundary services, such as quality attributes and capability attributes. We propose a two-phase quality design method for transboundary services called value quality deployment-quality capability deployment (VQD-QCD) based on quality function deployment (QFD). Given the restrictions of transboundary services, VQD-QCD translates the value expectations of multiple stakeholders into an optimal configuration for global quality parameters (GQPs), local quality parameters, and capability parameters. Details of VQD are illustrated. Considering the inherent vagueness and uncertainty of relationships between value expectations and GQPs, and among GQPs, fuzzy least absolute regression and fuzzy nonlinear programming methods are incorporated into QFD to identify the quantitative relations between value indicators and GQPs, and among GQPs, and obtain an optimal configuration scheme for GQPs. Usability of the proposed method is validated through a case study on the "DiDi mobile transportation service", which is a representative transboundary service in China. Compared with the current method, which is inaccurate and inefficient because its translation between value expectations and relevant quality and capability parameters is artificial and subjective, the proposed method integrates fuzzy least absolute regression and fuzzy nonlinear programming methods into QFD, which facilitate transboundary service designers to precisely and efficiently design the quality and capability characteristics of innovative services in th

关键词： nonlinear programming

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