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JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY 2023年第3期38卷 1893-1906页

作者： Demir, Yunus Keskin, M. Emre Bursa Tech Univ Engn & Nat Sci Fac Dept Ind Engn Bursa Turkiye Ataturk Univ Engn Fac Dept Ind Engn TR-06680 Erzurum Turkiye

Graphical/Tabular Abstract The supermarket chain discussed in this study addresses middle class customers in Turkey with 20 distribution centers (DC) and 3500 stores in 72 provinces. An average of 1500 items are sold in each store of the company. There is a great fluctuation in the demand from stores to DCs due to factors such as the presence of promotional products, seasonality and trends. Figure A shows the change in order quantity (in terms of pallets) between June and September when a store moves to its DC. In this study, the problem of creating a shipment plan for DCs is discussed in order to minimize these negative effects of variability.

关键词： Collaboration strategies Two level vendor managed inventory linear programming Heuristics

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An Efficient Dual-Parameter Full Waveform Inversion for GPR Data Using Data Encoding

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2023年 61卷

作者： Feng, Deshan Li, Bingchao Wang, Xun Ding, Siyuan Tai, Xiaoyong Cai, Liqiong Su, Xuan Cent South Univ Sch Geosci & Infophys Changsha 410083 Peoples R China Fuzhou City Construct Design & Res Inst Co Ltd Fuzhou 350001 Peoples R China

Ground penetrating radar (GPR) is an important shallow electromagnetic nondestructive detection technology. The full waveform inversion (FWI) of GPR data utilizes all information, including dynamics and kinematics, theoretically has the highest imaging accuracy, and meets the increasingly sophisticated needs of engineering exploration imaging. However, the bottleneck restricting the FWI is the low calculation efficiency, which cannot meet the requirements of rapid reconstruction of underground medium in actual engineering. In order to improve the calculation efficiency, we introduce the data encoding into the GPR dual-parameter FWI. Data encoding often brings crosstalk noise, and the noise is closely related to the encoding methods and data types. For this reason, we select the encoding of the crosshole data, wide-angle reflection and refraction data, and common-offset data for inversion. The experiments show that data encoding can effectively reduce computing time, and three different GPR data require different encoding methods due to their different redundancies. Total variation (TV) regularization can suppress the noise caused by data encoding. Although it will slightly increase the calculation time, it can significantly improve the inversion quality.

关键词： Encoding TV Mathematical models Crosstalk linear programming Data models Conductivity Data encoding dual parameter full waveform inversion (FWI) ground penetrating radar (GPR) total variation (TV) regularization

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Unit Commitment Problem with Energy Storage Under Correlated Renewables Uncertainty

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OPERATIONS RESEARCH 2023年第6期71卷 1960页

作者： Cordera, Felipe Moreno, Rodrigo Ordonez, Fernando Univ Chile Fac Phys & Math Sci Santiago 8330111 Chile MIT Operat Res Ctr Cambridge MA 02142 USA Inst Sistemas Complejos Ingn Santiago 8370398 Chile

The extensive integration of renewable generation in electricity systems is significantly increasing the variability and correlation in power availability and the need for energy storage capacity. This increased uncertainty and storage capacity should be considered in operational decisions such as the short-term unit commitment (UC) problem. In this work, we formulate a day-ahead UC problem with energy storage, considering multistage correlated uncertainty on renewables' power availability. We solve this multistage stochastic unit commitment (MSUC) problem with integer variables in the first stage using a new variant of SDDP that can explicitly deal with temporal correlations. Our computational results on the IEEE 118-bus system demonstrate the significance of considering multistage uncertainty and correlations, comparing our solution with other multistage solutions, two-stage solutions, and deterministic solutions typically used by industry. We also solve the MSUC problem for a representation of the Chilean power system, finding superior UC solutions for scenarios where adapting generation to the unfolding uncertainty is costly. Finally, we demonstrate that the MSUC approach can be used to define a more efficient deterministic UC solution, outperforming the current industry practice.

关键词： energy natural resources stochastic programming large-scale systems linear programming

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Minimum norm interpolation in the l1(N) space

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ANALYSIS AND APPLICATIONS 2021年第1期19卷 21-42页

作者： Cheng, Raymond Xu, Yuesheng Old Dominion Univ Dept Math & Stat Norfolk VA 23529 USA

We consider the minimum norm interpolation problem in the l(1)(N) space, aiming at constructing a sparse interpolation solution. The original problem is reformulated in the pre-dual space, thereby inducing a norm in a related finite-dimensional Euclidean space. The dual problem is then transformed into a linear programming problem, which can be solved by existing methods. With that done, the original interpolation problem is reduced by solving an elementary finite-dimensional linear algebra equation. A specific example is presented to illustrate the proposed method, in which a sparse solution in the l(1)(N) space is compared to the dense solution in the l(2)(N) space. This example shows that a solution of the minimum norm interpolation problem in the l(1)(N) space is indeed sparse, while that of the minimum norm interpolation problem in the l(2)(N) space is not.

关键词： Minimum norm interpolation duality linear programming sparsity

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Nesterov Acceleration for Equality-Constrained Convex Optimization via Continuously Differentiable Penalty Functions

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IEEE CONTROL SYSTEMS LETTERS 2021年第2期5卷 415-420页

作者： Srivastava, Priyank Cortes, Jorge Univ Calif San Diego Dept Mech & Aerosp Engn San Diego CA 92122 USA

We propose a framework to use Nesterov's accelerated method for constrained convex optimization problems. Our approach consists of first reformulating the original problem as an unconstrained optimization problem using a continuously differentiable exact penalty function. This reformulation is based on replacing the Lagrange multipliers in the augmented Lagrangian of the original problem by Lagrange multiplier functions. The expressions of these Lagrange multiplier functions, which depend upon the gradients of the objective function and the constraints, can make the unconstrained penalty function non-convex in general even if the original problem is convex. We establish sufficient conditions on the objective function and the constraints of the original problem under which the unconstrained penalty function is convex. This enables us to use Nesterov's accelerated gradient method for unconstrained convex optimization and achieve a guaranteed rate of convergence which is better than the state-of-the-art first-order algorithms for constrained convex optimization. Simulations illustrate our results.

关键词： Convex functions Acceleration Convergence linear programming Gradient methods Newton method Constrained optimization accelerated flows smooth exact penalty functions convex functions

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Model Predictive Control of Passive and Periodic Satellite Formation Based on linear programming Approach

Model Predictive Control of Passive and Periodic Satellite F...

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2014中国制导、导航与控制学术会议

作者： Guangyan Xu Tingting Yu Jianchao Wang Xia Chen Automation department Shenyang Aerospace University Shenyang 110136

ISBN: (纸本)9781479946983

This paper exploits the control algorithm design of fuel-optimal satellite formation keeping strategy using linear programming *** the study,a fuel-optimal control problem is converted into a linear programming problem by means of an approximate discretization ***,model predictive control approach is adopted to realize the fuel-optimal *** last,the designed control algorithm is applied to a satellite which maneuvers from an initial orbit to a passive and periodic relative orbit with minimal fuel *** results demonstrate the efficiency and rapidity of the proposed algorithm.

关键词： artificial satellites control system synthesis linear programming optimal control predictive control approximate discretization method control algorithm design designed control algorithm fuel-optimal control problem fuel-optimal maneuver fuel-optimal satellite formation keeping strategy linear programming problem minimal fuel consumption model predictive control periodic relative orbit periodic satellite formation Equations linear programming Mathematical model Optimal control Orbits Predictive control Satellites

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Finding the capacity of next-generation networks by linear programming

Finding the capacity of next-generation networks by linear p...

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International Conference on Communication Systems

作者： Chee Wei Tan Siu-Wai Ho Shan Lint Raymond W. Yeung College of Science and Engineering City University of Hong Kong Institute for Telecommunications Research University of South Australia Department of Information Engineering The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781479958337

Proving or disproving an information inequality is a crucial step in establishing the converse results in the coding theorems of communication networks. However, next-generation networks are very large-scale, typically involving multiple users and many transceivers and relays. This means that an information inequality involving many random variables can be difficult to be proved or disproved manually. In [1], Yeung developed a framework that uses linear programming for verifying linear information inequalities, and it was recently shown in [2] that this framework can be used to explicitly construct an analytic proof of an information inequality or an analytic counterexample to disprove it if the inequality is not true in general. In this paper, we consider the construction of the smallest counterexample, and also give sufficient conditions for that the inequality can be manipulated to become true. We also describe the software development of automating this analytical framework enabled by cloud computing to analytically verify information inequalities in large-scale problem setting.

关键词： Cramer-Rao bounds Next generation networks linear programming inequalities computer software Frameworks Counter example networks(communications) Random variable

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Optimisation sizing of hybrid wind-diesel systems using linear programming technique

Optimisation sizing of hybrid wind-diesel systems using line...

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7th IET International Conference on Power Electronics, Machines and Drives (PEMD 2014)

作者： Leong Kit Gan Jonathan K.H. Shek Markus A. Mueller The University of Edinburgh United Kingdom The University of Edinburgh Edinburgh Edinburgh GB

ISBN: (纸本)9781632666390

Despite the great potential of hybrid wind-diesel system in supplying energy to remote or island communities, sizing the system components have been a challenging problem for many project managers due to the reliance on various factors. This work considers utilising a fixed speed wind turbine (induction generator) in the hybrid system. It requires energy for start-up operation and this work takes into account for sizing the battery storage. In addition, the trade-off between the number of batteries and diesel generator fuel usage in a system is studied. linear programming for optimal sizing of batteries needed in a hybrid wind-diesel system, in the context of minimum diesel fuel usage is reported in this paper. Finally, this paper also shows that the storage capacity required in a hybrid system for various wind and load conditions can be computed in a systematic manner.

关键词： Hybrid wind-diesel system Sizing Optimisation linear programming Fixed speed wind turbine SIZING linear programming hybrid systems Batteries compound winding program technique wind turbine induction generator Storage capacity Secondary batteries fixed speed load conditions

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Lightweight digital video stabilization for small-size robot

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MECHATRONICS 2023年第1期94卷

作者： Vijayakumar, Adwaith Vachhani, Leena Gupta, Abhishek Indian Inst Technol Maharashtra 400074 India

Though constrained by payload and processing, small robots have gained applications in collecting visual information from the scene. Typically these small-size robots do not carry data loggers and send the video information to a hand-held device at a remote location for visual observations. Due to sophisticated processing and control limitations from mechatronics resources, the video captured by the robot is subjected to the effects of unintended motion, which requires digital methods for video stabilization. For a lightweight solution for video stabilization, we avoid use of any external hardware and develop a Singular Value Decomposition (SVD) based digital algorithm that avoids explicit feature tracking and motion estimation during stabilization. The process involves identifying a subspace with minimal dimensions that contains information of intentional motion alone. This work identifies the minimal subspace for video stabilization using the sliding window geometry method for practical implementation. Further, a shape-preserving filter is utilized to remove perturbations induced by the unintended motions, thereby resulting in the reconstruction of the stabilized video sequence. Experimental results on two different small-size robots viz spherical robot and Unmanned Aerial Vehicle (UAV) in indoor and outdoor settings, respectively, show quality outcomes without any change in parameters of the proposed filter design. Performance comparison with existing methods on the quality of stabilized video shows that the proposed stabilization method overcomes the non-availability of features for tracking due to large amplitudes and limited onboard resources. With the proposed video stabilization method, there is a potential for wider applicability of small-size robots in remote visual observations.

关键词： Video stabilization SVD linear programming Shape preserving filter Small-size mobile robot Spherical robots

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A novel renewable powered stand-alone electric vehicle parking-lot model

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2023年 33卷

作者： Jawad, Muhammad Asghar, Hira Arshad, Jehangir Javed, Abbas Qureshi, Muhammad Bilal Ali, Sahibzada Muhammad Shabbir, Noman Rassolkin, Anton COMSATS Univ Islamabad Dept Elect & Comp Engn Lahore Campus Islamabad 54000 Pakistan COMSATS Univ Islamabad Dept Elect & Comp Engn Abbottabad Campus Islamabad 22010 Pakistan Tallinn Univ Technol Dept Elect Power Engn & Mechatron EE-12616 Tallinn Estonia

Environmental and economic improvements prevailed by Electric Vehicles (EVs) cannot be fully achieved unless renewable energy sources partially or fully charge the EVs. However, due to the intermittent nature of renewable energy, it is challenging to rely solely on renewable energy. Previous works attempted to accurately predict renewable power generation considering the intermittent nature of temperature and wind, but adequate renewable power supply cannot always guarantee. To address this problem, we proposed a novel area-based EV parking-lot model for charge scheduling of EVs with a predefined Service Level Objective (SLO). Moreover, power demand of each area is fulfilled with distributed solar and wind generators whose probability to produce energy no less than the SLO of the parking-lot area and have predicted energy no less than that area's power demand. The Energy Storage Supply (ESS) is incorporated to ensure sufficient power to avoid SLO violations. Deep learning technique is used to predict the probability of generating renewable power no less than the power demand of the area for each EV parking-lot area. A linear optimization problem is formulated to map distributed renewable power generators to different parking-lot areas for minimization of SLO violations, total monetary cost of energy and carbon emission, and maximize the number of charged EVs at each time interval. The evaluation on real data traces shows that for 500 EV arrived per day case, our model is effective to minimize monetary cost of power consumption by 0.88% and carbon emission by 1.89% while having very less SLO violations in a day.(c) 2023 Elsevier Ltd. All rights reserved.

关键词： Demand response Electric vehicles Forecasting linear programming Optimization Smart grids

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