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21st International Conference on Mathematical Optimization Theory and Operations research, MOTOR 2022

作者： Vasilyev, Igor Rybin, Dmitry Kudria, Sergey Ren, Jie Zhang, Dong Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the Russian Academy of Sciences Irkutsk Russia Huawei Novosibirsk Research Center Novosibirsk Russia The Chinese University of Hong Kong Shenzhen China Huawei Moscow Research Center Moscow Russia Algorithm and Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd. Dongguan China

ISBN: (纸本)9783031096068

The paper addresses the Network Roll-Out (NRO) problem aimed at scheduling the construction of mobile stations. In this case, NRO problem can be considered as a generalization of Resource-Constrained Project Scheduling Problem, where we need to find a schedule for the activities related to the construction of a set of base stations taking into account the precedence constraints and the availability of resources while minimizing some measure of performance. The generalization involves the multiple projects, multi-modes, discrete time-cost tradeoff, together with particular business requirements like precedence redundancy and workload stability constraints. To solve this problem, we propose a MIP formulation that is based on a generalization of Disaggregated Discrete-Time formulation with pulse start variables. Using this formulation, we propose a three-stage heuristic based on a relax and fix strategy. The effectiveness and efficiency of the proposed approach are illustrated in a series of computational experiments on real-life problem instances. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Scheduling

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Incremental Model Predictive Control for Velocity-Controlled Robot Manipulators

Incremental Model Predictive Control for Velocity-Controlled...

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Annual Conference of Industrial Electronics Society

作者： Yongchao Wang Hengrui Li Cong Li Fangzhou Liu School of Aerospace Science and Technology Xidian University Xi’an China Algorithm Engineer Research and Development Department Agile Robots Beijing China College of Intelligence Science and Technology National University of Defense Technology Changsha China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In this article, an incremental model predictive controller is proposed for the velocity-controlled robot manipulator. First, the time-delay estimation (TDE) technique is used to approximate the unknown discrepancy between the command and the real joint velocity due to velocity dynamics, and the equation of motion in the incremental form is obtained. Then, on the basis of the resulting equation of motion and taking into account joint position and velocity constraints, the incremental model predictive controller is developed by formulating a constrained optimal control problem (OCP). The constrained OCP is cast to a quadratic programming (QP) problem, making it possible to employ computationally efficient QP solvers to solve the constrained OCP. As a result, real-time control is guaranteed. Finally, experiments on a robot manipulator are implemented to verify the effectiveness of the developed incremental model predictive controller.

关键词： Service robots Computational modeling Optimal control Estimation Predictive models Mathematical models Robustness Computational efficiency Quadratic programming Predictive control

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A Large Scale Extended algorithm for 2D Halton Points with Low-Discrepancy Sequences 3

A Large Scale Extended Algorithm for 2D Halton Points with L...

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3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Chen, Wenxing Dai, Shuyang Zheng, Baojuan Wuhan University School of Mathematics and Statistics Wuhan430072 China Commercial Vehicle Technology Center of SAIC Motor Group Co. Ltd Department of Algorithm Research and Development Shanghai200433 China

ISBN: (纸本)9781665417327

Random discrete points have important application value in meshless PDE equation discretization, molecular dynamics simulation, point cloud imaging and so on. There are many common methods to generate random points, such as Monte Carlo, Gibbs Sampling, and Hammersley series and etc. But Halton random point algorithm has a defect that it only generates discrete points in [0, 1]2 region. However, in practical applications, it is necessary to be able to generate discrete points on any area. This paper proposed a new Halton points extension algorithm to solve this defects. We defined a linear operator which can transform discrete points from [0, 1]2 region into any plane region. Two examples are given, the extension algorithm respectively includes square, rectangular and polar coordinates region. The numerical results show that our method is accurate, effective and more general, it also enhanced the application range by our method. © 2021 IEEE.

关键词： Molecular dynamics

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Digital twin channel: A data-driven continuous trajectory modeling 1

Digital twin channel: A data-driven continuous trajectory mo...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Yu, Zehao Lv, Xingzai Rui, Hua Lin, Wei ZTE Corporation State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China Algorithm Department Wireless Product Research and Development Institute ZTE Corporation Shanghai201203 China

ISBN: (纸本)9781665433372

Digital twin channel modeling is the core and the most challenging part of the digital twin communication systems, due to the complex and susceptible nature of the wireless channel. However, existing channel models are inadequate in capturing the characteristics of real-world channels where the user equipments (UEs) are moving. In this paper, we solve this problem by developing a data-driven continuous trajectory modeling, which requires only a limited number of channel measurements to generate continuous channel coefficients for arbitrary UE tracks. The proposed approach consists of two steps: (1) building a data-driven model which captures the spatial correlation of the wireless channel based on scenario-specific channel measurements, and (2) constructing a trajectory model which models the temporal correlation of channel parameters when the UE is moving. Simulation results show that the proposed modeling process generates channel models whose spatial and temporal characteristics well match the real-world wireless channels. © 2021 IEEE.

关键词： Trajectories

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RaftGP: Random Fast Graph Partitioning

RaftGP: Random Fast Graph Partitioning

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IEEE Conference on High Performance Extreme Computing (HPEC)

作者： Yu Gao Meng Qin Yibin Ding Li Zeng Chaorui Zhang Weixi Zhang Wei Han Rongqian Zhao Bo Bai Theory Lab 2012 Labs Central Research Institute Huawei Technologies Co. Ltd. Department of Computer Science & Engineering Hong Kong University of Science & Technology Algorithm & Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd.

Graph partitioning (GP), a.k.a. community detection, is a classic problem that divides the node set of a graph into densely-connected blocks. Following prior work on the IEEE HPEC Graph Challenge benchmark and recent advances in graph machine learning, we propose a novel RAndom FasT Graph Partitioning (RaftGP) method based on an efficient graph embedding scheme. It uses the Gaussian random projection to extract community-preserving features from classic GP objectives. These features are fed into a graph neural network (GNN) to derive low-dimensional node embeddings. Surprisingly, our experiments demonstrate that a randomly initialized GNN even without training is enough for RaftGP to derive informative community-preserving embeddings and support high-quality GP. To enable the derived embeddings to tackle GP, we introduce a hierarchical model selection algorithm that simultaneously determines the number of blocks and the corresponding GP result. We evaluate RaftGP on the Graph Challenge benchmark and compare the performance with five baselines, where our method can achieve a better trade-off between quality and efficiency. In particular, compared to the baseline algorithm [1] of the IEEE HPEC Graph Challenge, our method is 6.68x - 23.9x faster on graphs with 1E3 - 5E4 nodes and at least 64.5x faster on larger (IE5 node) graphs on which the baseline takes more than 1E4 seconds. Our method achieves better accuracy on all test cases. We also develop a new graph generator to address some limitations of the original generator in the benchmark.

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A NOVEL APPROACH FOR HOLOGRAPHIC 3D CONTENT GENERATION WITHOUT DEPTH MAP

arXiv

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arXiv 2023年

作者： Kim, Hakdong Jee, Minkyu Lee, Yurim Choi, Kyudam Yoon, MinSung Kim, Cheongwon Department of Digital Contents Sejong University Seoul05006 Korea Republic of Department of Algorithm Development Selvers Seoul04594 Korea Republic of Department of Software Sejong University Seoul05006 Korea Republic of Department of Software Convergence Sejong University Seoul05006 Korea Republic of Communication & Media Research Laboratory Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of

In preparation for observing holographic 3D content, acquiring a set of RGB color and depth map images per scene is necessary to generate computer-generated holograms (CGHs) when using the fast Fourier transform (FFT) algorithm. However, in real-world situations, these paired formats of RGB color and depth map images are not always fully available. We propose a deep learning-based method to synthesize the volumetric digital holograms using only the given RGB image, so that we can overcome environments where RGB color and depth map images are partially provided. The proposed method uses only the input of RGB image to estimate its depth map and then generate its CGH sequentially. Through experiments, we demonstrate that the volumetric hologram generated through our proposed model is more accurate than that of competitive models, under the situation that only RGB color data can be provided. Copyright © 2023, The Authors. All rights reserved.

关键词： Holograms

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RaftGP: Random Fast Graph Partitioning

arXiv

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arXiv 2023年

作者： Gao, Yu Qin, Meng Ding, Yibin Zeng, Li Zhang, Chaorui Zhang, Weixi Han, Wei Zhao, Rongqian Bai, Bo Theory Lab Central Research Institute 2012 Labs Huawei Technologies Co. Ltd China Algorithm & Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd. China Department of Computer Science & Engineering Hong Kong University of Science & Technology Hong Kong

Graph partitioning (GP), a.k.a. community detection, is a classic problem that divides the node set of a graph into densely-connected blocks. Following prior work on the IEEE HPEC Graph Challenge benchmark and recent advances in graph machine learning, we propose a novel RAndom FasT Graph Partitioning (RaftGP) method based on an efficient graph embedding scheme. It uses the Gaussian random projection to extract community-preserving features from classic GP objectives. These features are fed into a graph neural network (GNN) to derive low-dimensional node embeddings. Surprisingly, our experiments demonstrate that a randomly initialized GNN even without training is enough for RaftGP to derive informative community-preserving embeddings and support high-quality GP. To enable the derived embeddings to tackle GP, we introduce a hierarchical model selection algorithm that simultaneously determines the number of blocks and the corresponding GP result. We evaluate RaftGP on the Graph Challenge benchmark and compare the performance with five baselines, where our method can achieve a better trade-off between quality and efficiency. In particular, compared to the baseline algorithm [1] of the IEEE HPEC Graph Challenge, our method is 6.68x – 23.9x faster on graphs with 1E3 – 5E4 nodes and at least 64.5x faster on larger (1E5 node) graphs on which the baseline takes more than 1E4 seconds. Our method achieves better accuracy on all test cases. We also develop a new graph generator to address some limitations of the original generator in the benchmark. Copyright © 2023, The Authors. All rights reserved.

关键词： Graph neural networks

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Fast Heuristic algorithms for the Multiple Strip Packing Problem 1

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20th International Conference on Mathematical Optimization Theory and Operations research , MOTOR 2021

作者： Vasilyev, Igor Ushakov, Anton V. Barkova, Maria V. Zhang, Dong Ren, Jie Chen, Juan Matrosov Institute for System Dynamics and Control Theory of SB RAS 134 Lermontov Street Irkutsk664033 Russia Algorithm and Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd. Dongguan China Moscow Advanced Software Technology Lab Huawei Russian Research Institute Moscow Russia

ISBN: (数字)9783030864330

ISBN: (纸本)9783030864323

In this paper we address the so-called two-dimensional Multiple Strip Packing Problem (MSPP). There is a set of rectangles and a set of strips, where each strip has a pre-defined width. The problem is to find a feasible packing of all the rectangles into the strips so as the maximal height of the packing over all the strips is minimized. A packing is feasible if all the rectangles are placed into the strips and not overlapped. In case of only one strip, the problem is widely known as the Strip Packing Problem (SPP). Many effective constructive heuristics for SPP are based on the so-called skyline representation of a packing pattern. We generalized this approach for the case of multiple strips and developed a randomized local search, which embeds the proposed skyline heuristic to compute the objective value for a packing. We also introduced the two-dimensional level multiple strip packing problem and developed some level-based constructive heuristics. We report computational results on real-life problem instances arisen in an application of MSPP in scheduling computing jobs on multiple Spark computer clusters. © 2021, Springer Nature Switzerland AG.

关键词： Heuristic algorithms

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Decomposition and comparative analysis of urban-rural differences in eHealth literacy among nursing students: A multisite cross-sectional study

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Nurse Education Today 2025年 146卷 106562页

作者： Wang, Xue Ge, Lina Yu, Zhenjie Qiao, Qiao Guo, Xiaoming Liu, Shiping Zhang, Chengcai Zang, Shuang Department of Community Nursing School of Nursing China Medical University Shenyang China Department of Obstetrics and Gynecology Shengjing Hospital of China Medical University Shenyang China School of Nursing Tianjin Medical University Tianjin China Department of Radiation Oncology The First Hospital of China Medical University Shenyang China Algorithm Research and Development Department Neusoft IntelliRay Technology Co. Ltd. Shenyang China

Background: Investigating the urban-rural differences in eHealth literacy among Chinese nursing students is imperative for enhancing healthcare education and practice. This study aimed to investigate the factors that contribute to urban-rural differences in eHealth literacy among Chinese nursing students and measure their respective contributions. Design: A multisite cross-sectional study. Settings: In China. Participants: A total of 967 nursing students were involved in this study. Methods: Multivariate linear regression models were used to explore the associations between sociodemographic and health-related factors and the eHealth literacy of Chinese nursing students. Additionally, Blinder-Oaxaca decomposition was employed to scrutinize the factors attributing to the urban-rural differences in eHealth literacy among Chinese nursing students, elucidating their respective contributions. Results: The mean eHealth literacy score for urban nursing students (mean: 20.26, SD: 3.61) exceeded that of rural nursing students (mean: 19.53, SD: 3.56) (p < 0.001). Blinder-Oaxaca decomposition analysis indicated that 84.82 % of the urban-rural differences in eHealth literacy among nursing students can be explained. The urban-rural differences are primarily explained by family health (40.05 %). Conclusions: The study emphasizes the importance of tailoring educational curricula to address urban-rural differences in eHealth literacy among nursing students in China. Specifically, incorporating content related to family health in educational programs is crucial. © 2024 Elsevier Ltd

关键词： China Comparative analysis Decomposition analysis eHealth literacy Nursing students Urban-rural difference

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Integer Programming Approach to the Data Traffic Paths Recovering Problem 19th

Integer Programming Approach to the Data Traffic Paths Recov...

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19th International Conference on Mathematical Optimization Theory and Operations research, MOTOR 2020

作者： Vasilyev, Igor Zhang, Dong Ren, Jie Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of Sciences Irkutsk Russia Algorithm and Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd. Dongguan China Moscow Advanced Software Technology Lab Huawei Russian Research Institute Moscow Russia

ISBN: (纸本)9783030499877

In this paper, we propose a novel approach to recovering path relationships in communication networks. The path relationship is one of the key input data which is necessary for network operation and maintenance. We have a continuous network transformation, upgrades, expansions, service allocations, thus the network physical topology and paths relationship are permanently changing with high frequency. Our approach is aimed at recovering the path relationships through flow information of each arc in the network. Getting the flow information is not a big technical problem and its control is included in the basic toolbox for network monitoring. We consider two scenarios which lead us to integer linear programs. The both of them minimize the flow deviation, where in the first one we look for a directed spanning tree (r-arborescence) and, in the second one—more general origin/destination paths (OD-paths). We propose mixed integer linear programming formulations for both problems. Their feature is that they contain the non-polynomial number of constraints which are considered implicitly by the cutting planes approach. The preliminary computation results showed that the large-scale instances of the first scenario can easily be solved. At the same time, the optimal solutions of second scenario problems can be found only on small- and medium-size instances, which inspires for the further research. © 2020, Springer Nature Switzerland AG.

关键词： Integer programming

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