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Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 2018年 195卷 118-131页

作者： Haddadsisakht, Ali Ryan, Sarah M. Wise Syst Inc Cambridge MA USA Iowa State Univ Dept Ind & Mfg Syst Engn Ames IA 50011 USA

We optimize the design of a closed-loop supply chain network that encompasses flows in both forward and reverse directions and is subject to uncertainty in demands for both new and returned products. The model also accommodates a carbon tax with tax rate uncertainty. The proposed model is a three-stage hybrid robust/stochastic program that combines probabilistic scenarios for the demands and return quantities with uncertainty sets for the carbon tax rates. The first stage decisions are facility investments, the second stage concerns the plan for distributing new and collecting returned products after realization of demands and returns, and the numbers of transportation units of various modes are the third stage decisions. The second- and third-stage decisions may adjust to the realization of the carbon tax rate. For computational tractability, we restrict them to be affine functions of the carbon tax rate. Benders cuts are generated using recent duality developments for robust linear programs. Computational results-show that adjusting product flows to the tax rate provides negligible benefit, but the ability to adjust transportation mode capacities can substitute for building additional facilities as a way to respond to carbon tax uncertainty.

关键词： Affinely adjustable robust counterpart Closed-loop supply chain Scenario-based optimization Benders decomposition semi-definite programming

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Optimal Long-Term Distributed Generation Planning and Reconfiguration of Distribution Systems: An Accelerating Benders' Decomposition Approach

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2018年第1期179卷 283-310页

作者： Khodayifar, Salman Raayatpanah, Mohammad A. Rabiee, Abbas Rahimian, Hamed Pardalos, Panos M. IASBS Dept Math Gavazang Rd Zanjan Iran Kharazmi Univ Fac Math Sci & Comp Tehran Iran Univ Zanjan Dept Elect Engn Zanjan Iran Ohio State Univ Dept Integrated Syst Engn Columbus OH 43210 USA Univ Florida Dept Ind & Syst Engn Ctr Appl Optimizat Gainesville FL 32611 USA

In this paper, we study the multi-period distributed generation planning problem in a multistage hierarchical distribution network. We first formulate the problem as a non-convex mixed-integer nonlinear programming problem. Since the proposed model is non-convex and generally hard to solve, we convexify the model based on semi-definite programming. Then, we use a customized Benders' decomposition method with valid cuts to solve the convex relaxation model. Computational results show that the proposed algorithm provides an efficient way to solve the problem for relatively large-scale networks.

关键词： Combinatorial optimization Distributed generation Multi-period optimal power flow Non-convex mixed-integer nonlinear programming semi-definite programming Benders' decomposition

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Nuclear Norm Subspace Identification Of Continuous Time State-Space Models

Nuclear Norm Subspace Identification Of Continuous Time Stat...

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5th IFAC Conference on Advances in Control and Optimization of Dynamical Systems (ACODS)

作者： Varanasi, Santhosh Kumar Jampana, Phanindra Indian Inst Technol Hyderabad Dept Chem Engn Sangareddy 502285 Telangana India

Subspace identification techniques derive approximate models rather than models that are optimal with respect to a goodness of fit criterion. To obtain low rank models, a nuclear norm minimization method for estimating the system matrices of linear time invariant continuous time state-space models in the presence of measurement noise is proposed. In the proposed approach, Generalized Poisson Moment Functional (GPMF) method is used to circumvent the time-derivative problem which is inherent in continuous time models. To make the proposed algorithm consistent, instrumental variables (Hankel matrix of past inputs) are considered. The accuracy of the proposed method is demonstrated with the help of numerical simulations on a variety of systems. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： System Identification Nuclear Norm Minimization Continuous Time State-Space Models Generalized Poisson Moment Functionals semi-definite programming

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Demixing sines and spikes: Robust spectral super-resolution in the presence of outliers

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INFORMATION AND INFERENCE-A JOURNAL OF THE IMA 2018年第1期7卷 105-168页

作者： Fernandez-Granda, Carlos Tang, Gongguo Wang, Xiaodong Zheng, Le NYU Courant Inst Math Sci Ctr Data Sci 251 Mercer St New York NY 10003 USA Colorado Sch Mines Dept Elect Engn & Comp Sci 1500 Illinois St Golden CO 80401 USA Columbia Univ Dept Elect Engn 116th St & Broadway New York NY 10027 USA

We consider the problem of super-resolving the line spectrum of a multisinusoidal signal from a finite number of samples, some of which may be completely corrupted. Measurements of this form can be modeled as an additive mixture of a sinusoidal and a sparse component. We propose to demix the two components and super-resolve the spectrum of the multisinusoidal signal by solving a convex program. Our main theoretical result is that-up to logarithmic factors-this approach is guaranteed to be successful with high probability for a number of spectral lines that is linear in the number of measurements, even if a constant fraction of the data are outliers. The result holds under the assumption that the phases of the sinusoidal and sparse components are random and the line spectrum satisfies a minimum-separation condition. We show that the method can be implemented via semi-definite programming, and explain how to adapt it in the presence of dense perturbations as well as exploring its connection to atomic-norm denoising. In addition, we propose a fast greedy demixing method that provides good empirical results when coupled with a local non-convex-optimization step.

关键词： atomic norm continuous dictionary convex optimization greedy methods line spectra estimation outliers semi-definite programming sparse recovery super-resolution

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An Exact SOCP Formulation for AC Optimal Power Flow 20

An Exact SOCP Formulation for AC Optimal Power Flow

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20th National Power Systems Conference (NPSC)

作者： Yasasvi, P. Naga Chandra, Snehil Mohapatra, A. Srivastava, S. C. Indian Inst Technol Kanpur Dept Elect Engn Kanpur 208016 Uttar Pradesh India

ISBN: (纸本)9781538661598

AC Optimal Power Flow (ACOPF) formulation, in general, is nonlinear and non-convex in nature and hence its application to problems like robust system operation, optimal transmission switching, etc. is a herculean task. Convexification of OPF is desired in order to reduce the complexity of solving such problems. Existing convex formulations such as semi-definite programming (SDP), conventional Second Order Conic programming (SOCP), and so on and their variants result either in significant optimality gap (OG) or reduced OG, albeit with the presence of non-convexity or approximations which bridge the gap between convexity and non-convexity. Due to these challenges, the current practice in the electricity sector is still to use the DCOPF (approximation of ACOPF). Hence in this paper, an exact and novel SOCP formulation of actual ACOPF has been proposed which aims for getting an equivalent convex formulation similar to the actual nonlinear, non-convex ACOPF. This also ensures attaining zero OG for mesh as well as radial networks and hence, the possibility of easily integrating this formulation in OPFs with data uncertainty. The proposed methodology has been tested on a 3 bus, IEEE 14 bus and IEEE 118 bus test systems on GAMS platform. The results thus obtained, have been compared with those obtained from DCOPF, nonlinear, non-convex ACOPF, conventional SOCP formulation for radial networks (SOCP-I) and conventional SOCP formulation for mesh networks (SOCP-II). The results ensure zero OG of the proposed SOCP formulation.

关键词： Optimal power flow convexification semi-definite programming second order conic programming optimality gap

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Real Time Localization Algorithm based on Local Linear Embedding Optimization in Mobile Sensor Networks

Real Time Localization Algorithm based on Local Linear Embed...

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2019 7th International Conference on Machinery,Materials and Computing Technology(ICMMCT 2019)

作者： Huang Lili Department of Communication and Information Jiangxi Environmental Engineering Vocational College

Location accuracy of wireless sensor network relies on noise level and connection of non-line of ***,Location correcting algorithm based on semi-definite programming is proposed and it is based on edge-semi-definite programming;it is denoted as ESDP algorithm and it aims to increase location precision and reduce location time in severe *** algorithm is modified and robustness of ESDP algorithm in high error environment of distance measurement is increased for ESDP algorithm through quoting dithering *** algorithm handles high noise and deviation of non-line of sight through seeking low-rank *** result indicates that location precision of ESDP algorithm is better than algorithms of the same kind and calculation complexity is also reduced in environment of high noise and that most distance measurement is non-line of sight.

关键词： Wireless sensor network Location semi-definite programming Non-line of sight Robust

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semi-definite programming for Distributed Tracking of Dynamic Objects by Nonlinear Sensor Network

Semi-definite Programming for Distributed Tracking of Dynami...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Rashid, U. Tuan, H. D. Kha, H. H. Nguyen, H. H. Univ New S Wales Sydney NSW Australia

ISBN: (纸本)9781457705397

This paper discusses dynamic state estimation for nonlinear measurement model through distributed multisensor network under power constraints. For this scenario, we propose an optimized power allocation strategy based on semidefinite programming, that achieves minimum mean-squared error for the estimate subject to constraints on total transmit power. System nonlinearity is handled effectively with the help of distributed unscented Kalman filtering and linear fractional transformation. Furthermore, advantage of using multiple sensors over a single independent sensor is established through simulation results for tracking a maneuvering target.

关键词： Nonlinear sensor network unscented transformation semi-definite programming distributed linear fractional transformation filtering

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LINEARLY CONVERGENT FIRST-ORDER ALGORITHMS FOR semidefinite programming

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Journal of Computational Mathematics 2017年第4期35卷 452-468页

作者： Cong D. Dang Guanghui Lan Zaiwen Wen Department of Industrial and Systems Engineering University of Florida Gainesville FL 32611 H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of TechnologyAtlanta GA 30332 USA Beijing International Center for Mathematical Research Peking University Beijing 100871 China

In this paper, we consider two different formulations （one is smooth and the other one is nonsmooth） for solving linear matrix inequalities （LMIs）, an important class of semidefinite programming （SDP）, under a certain Slater constraint qualification assumption. We then propose two first-order methods, one based on subgradient method and the other based on Nesterov＇s optimal method, and show that they converge linearly for solving these formulations. Moreover, we introduce an accelerated prox-level method which converges linearly uniformly for both smooth and non-smooth problems without requiring the input of any problem parameters. Finally, we consider a special case of LMIs, i.e., linear system of inequalities, and show that a linearly convergent algorithm can be obtained under a much weaker assumption.

关键词： semi-definite programming Linear Matrix Inequalities Error Bounds Linear Convergence

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Navigation by inertial device and signals of opportunity

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SIGNAL PROCESSING 2017年第0期131卷 280-287页

作者： Simkovits, Haim Weiss, Anthony J. Amar, Alon Tel Aviv Univ Sch Elect Engn IL-69978 Tel Aviv Israel Technion Fac Elect Engn Haifa Israel

Inertial navigation systems are known to yield rather accurate measurements over short time intervals, while their error variance tends to increase with time. In order to keep the error within specification most systems use GPS signals. In the absence of GPS data, due to jamming or spoofing, it is desirable to use signals of opportunity instead. We examine the use of time of arrival measurements of signals of opportunity that have known structure. We propose a low complexity semi-definite relaxation algorithm by converting the maximum likelihood location estimator to a convex optimization problem. Simulation results demonstrate that the proposed algorithms converge to the Cramer-Rao lower bound under some geometrical and noise limitations. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Inertial navigation system Time of arrival Maximum likelihood estimator Signals of opportunity semi-definite programming

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A Two-Way Network Beamforming Approach Based on Total Power Minimization With Symmetric Relay Beamforming Matrices

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IEEE ACCESS 2017年 5卷 12458-12474页

作者： Rahimi, Razgar Shahbazpanahi, Shahram Univ Ontario Inst Technol Dept Elect Comp & Software Engn Oshawa ON L1H 7K4 Canada

We study the total transmit power minimization problem for a two-way relay network under two constraints on the transceivers' received signal-to-noise-ratios. The network considered herein consists of multiple multi-antenna relay nodes and two single-antenna transceivers. Each relay transforms the vector of its received signals, by multiplying this vector with a complex beamforming matrix, thereby obtaining a new vector whose entries are transmitted over different antennas of that relay. Assuming the relay beamforming matrices and the transceivers' transmit powers as the design parameters, we first study the total power minimization problem under the assumption that the relay beamforming matrices are symmetric. Under such an assumption, we show that the total power minimization problem is amenable to a semi-closed-form solution, and thus, it can be solved efficiently. We then consider the case, where the relay beamforming matrices may not be symmetric and show that in this case, the total power minimization problem can be solved using a computationally prohibitive algorithm which involves a 2-D search over a grid in the space of the transceivers' transmit powers and semi-definite programming at each vertex of this grid. Our numerical results show that the symmetric assumption on the relay beamforming matrices incurs only insignificant loss, while this assumption allows us to significantly reduce the computational burden of solving the total power minimization problem.

关键词： MIMO relaying two-way relay networks bidirectional relay networks total power minimization symmetric relay beamforming network beamforming semi-definite programming

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