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A Splicing Approach to Best Subset of Groups Selection

INFORMS JOURNAL ON COMPUTING 2023年第1期35卷 104-119页

作者： Zhang, Yanhang Zhu, Junxian Zhu, Jin Wang, Xueqin Renmin Univ China Sch Stat Beijing 100872 Peoples R China Sun Yat Sen Univ Southern China Ctr Stat Sci Sch Math Dept Stat Sci Guangzhou 510275 Peoples R China Natl Univ Singapore Saw Swee Hock Sch Publ Hlth Singapore 117549 Singapore Univ Sci & Technol China Int Inst Finance Sch Management Dept Stat & Finance Hefei 230026 Peoples R China

Best subset of groups selection (BSGS) is the process of selecting a small part of nonoverlapping groups to achieve the best interpretability on the response variable. It has attracted increasing attention and has far-reaching applications in practice. However, due to the computational intractability of BSGS in high-dimensional settings, developing efficient algorithms for solving BSGS remains a research hotspot. In this paper, we propose a group -splicing algorithm that iteratively detects the relevant groups and excludes the irrelevant ones. Moreover, coupled with a novel group information criterion, we develop an adaptive algorithm to determine the optimal model size. Under certain conditions, it is certifiable that our algorithm can identify the optimal subset of groups in polynomial time with high probability. Finally, we demonstrate the efficiency and accuracy of our methods by compar-ing them with several state-of-the-art algorithms on both synthetic and real-world data sets.

关键词： best subset of groups selection group splicing group information criterion selection consistency of subset of groups polynomial computational complexity

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Minimizing makespan of a production batch within concurrent systems:Seru production perspective

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Journal of Management Science and Engineering 2022年第1期7卷 1-18页

作者： Yin Gai Yong Yin Jiafu Tang Shiqiang Liu College of Management Science and Engineering Dongbei University of Finance and EconomicsDalian116025China Graduate School of Business Doshisha UniversityKyoto602-8580Japan School of Economics and Management Fuzhou UniversityFuzhou350108China

This paper discusses the makespan minimization of a production batch within a specific concurrent system,seru production system.A seru production system consists of multiple independent serus.A seru is a compact assembly origination in which products are assembled from-the-beginning-to-the-end without *** capability of a seru production system is its responsiveness.A performance measure used to evaluate a seru system’s responsiveness is the makespan of production batches assembled within the seru *** study addresses the makespan minimization problem through an optimal seru loading *** problem is formulated as a min-max integer optimization *** exact dimension-reduction Algorithm is developed to obtain the optimal allocation that minimizes the *** show that the solution space increases very *** contrast,our algorithm is efficient with a polynomial computational complexity of,where is the total number of serus in a seru *** verify the usefulness of the developed exact dimension-reduction algorithm,we compare it with a widely practiced greedy algorithm through *** find that our optimal algorithm is robust in most cases and the greedy algorithm is efficient when variability in production efficiencies is *** result can guide us to adopt different algorithms in different business *** the variability in production efficiencies is high,e.g.,new employees and/or new products assembly,the greedy algorithm is *** other cases,our optimal algorithm should be adopted to obtain the minimum *** also extend the method to the application of a rotating seru.

关键词： Assembly Greedy algorithm Dimension reduction Exact algorithm Variability polynomial computational complexity

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Energy-Efficient Power Allocation Maximization With Mixed Group Sum Power Bound and QoS Constraints

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第10期67卷 7139-7151页

作者： He, Peter Dong, Min Ontario Tech Univ Dept Elect Comp & Software Engn Oshawa ON L1G 0C5 Canada

Energy efficiency (EE) is a critical performance measure in the next generation wireless communication systems, especially for battery-constrained Internet of Things (IoT) devices. We investigate the power allocation optimization problem in a multi-channel wireless system for EE maximization, subject to the sum power and the throughput constraints over each group of assigned channels, as well as the total power constraint. Resorting to geometric interpretation on the constraints, we propose the group virtually ceiled and bottomed water-filling (GVC-WF) algorithm to solve this EE maximization problem. Our proposed algorithm computes the exact optimal solution with a quadratic polynomial computational complexity. With the optimality and computational advantages, our proposed algorithm is suitable for power allocation in large-scale wireless systems. Simulation results demonstrate that our proposed power allocation algorithm improves the energy efficiency by more than 40%, as compared to the conventional Dinkelbach's method with the same amount of computations.

关键词： Energy efficiency exact solution geometric water-filling power allocation non-linear fractional optimization polynomial computational complexity

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Energy-Efficient Power Allocation With Individual and Sum Power Constraints

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2018年第8期17卷 5353-5366页

作者： He, Peter Zhang, Shan Zhao, Lian Shen, Xuemin Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Beihang Univ Sch Comp Sci & Engn Beijing Key Lab Comp Networks Beijing 100191 Peoples R China Ryerson Univ Dept Elect & Comp Engn Toronto ON M5B 2K3 Canada

In this paper, we investigate the power allocation in a multi-user wireless system to maximize the energy efficiency, while meeting the power constrains of each individual user and the whole system. Specifically, a geometric ceiled-water-filling algorithm is proposed to solve this non-linear fractional optimization problem, which can compute exact solutions with a low degree of polynomial computational complexity. Optimality of the proposed algorithm is strictly proved with mathematical analysis. In addition, the proposed algorithm is further extended to the general case with the minimum system-level throughput constraint, considering the quality of service requirement. To the best of our knowledge, no prior algorithm in the open literature offered such optimal solutions to the target problems, with the merit of exactness and the efficiency. Simulation results demonstrate that the proposed power allocation algorithms can improve the energy efficiency by nearly 50%, compared with the conventional Dinkelbach's method with the same amount of computations.

关键词： Energy efficiency (EE) exactness geometric water-filling (GWF) non-linear fractional optimization polynomial computational complexity power allocation

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Cognitive radar sequence design under the spectral compatibility requirements

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IET RADAR SONAR AND NAVIGATION 2017年第5期11卷 759-767页

作者： Ge, Peng Cui, Guolong Karbasi, Seyyed Muhammad Kong, Lingjiang Yang, Jianyu Univ Elect Sci & Technol China Sch Elect Engn Chengdu Sichuan Peoples R China Sharif Univ Technol Dept Elect Engn Tehran *** Iran

As the increasing demands of military detection, wireless communication and remote sensing make the spectrum even more crowded, radar sequence design meeting spectral compatibility requirement is a challenging and urgent problem. This study is devoted to designing optimised phase-coded sequences which keep spectral-compatible with the overlaid electromagnetic radiators and at the same time optimise the signal-to-interference-plus-noise ratio (SINR). First, an intelligent dynamic spectrum information around the radar system is achieved by a radio environmental map. The information is introduced to form a constrained optimisation process aimed at improving the spectral compatibility and the radar detection performance. Second, the unimodularity requirement is necessary to make full use of transmit power and a similarity constraint is enforced to keep desired ambiguity function feature. Third, to resolve the resulting non-convex optimisation quadratically constrained quadratic problem, a relaxation and a randomisation procedure are applied. Therefore, the technique behaves a polynomial computational complexity. Finally, the performance analysis is given to show its effectiveness in terms of the SINR, the spectral shape, and the resulting auto-correlation function.

关键词： phase coding radar detection concave programming quadratic programming computational complexity cognitive radar sequence design spectral compatibility requirement military detection wireless communication remote sensing optimised phase-coded sequences electromagnetic radiators signal-to-interference-plus-noise ratio SINR optimisation intelligent dynamic spectrum information radio environmental map constrained optimisation process radar detection performance unimodularity requirement transmit power similarity constraint ambiguity function feature nonconvex optimisation quadratically-constrained quadratic problem randomisation procedure relaxation procedure polynomial computational complexity spectral shape autocorrelation function

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Efficient optimal deadlock control of flexible manufacturing systems

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IET CONTROL THEORY AND APPLICATIONS 2016年第10期10卷 1181-1186页

作者： Han, Libin Xing, Keyi Zhou, Mengchu Chen, Xiao Gao, Zhenxin Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian Peoples R China Xi An Jiao Tong Univ Syst Engn Inst Xian Peoples R China China Elect Grp Corp Res Inst 28 Nanjing Jiangsu Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA King Abdulaziz Univ Renewable Energy Res Grp Jeddah Saudi Arabia

The development of an efficient deadlock avoidance policy (DAP) is a critical step in the design and operation of a flexible manufacturing system (FMS). However, even for a simple FMS, the computation of an optimal DAP is intractable. This work addresses the optimal deadlock control problem of FMSs. Based on their Petri net models, it introduces the concept of -resources and proves that an FMS containing no -resources has only two types of reachable states: safe ones and deadlocks. It then can obtain an optimal DAP with polynomial computational complexity for a broader class of FMSs, which was never seen before. At the same time, for these FMSs, new structurally simpler optimal Petri net controllers are proposed.

关键词： flexible manufacturing systems optimal control Petri nets computational complexity flexible manufacturing systems FMS deadlock avoidance policy optimal DAP Petri net models -resources polynomial computational complexity reachable states

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Direct algorithm for the solution of two-sided obstacle problems with M-matrix

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NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS 2011年第1期18卷 167-173页

作者： Jiang, Ying-Jun Zeng, Jin-Ping Changsha Univ Sci & Technol Coll Math & Computat Sci Changsha 410004 Hunan Peoples R China Dongguan Univ Technol Coll Comp Dongguan 523005 Guangdong Peoples R China

A direct algorithm for the solution to the affine two-sided obstacle problem with an M-matrix is presented. The algorithm has the polynomial bounded computational complexity O(n(3)) and is more efficient than those in... 详细信息

关键词： two-sided obstacle problem direct algorithm M-matrix polynomial computational complexity

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Finding Patterns in Labeled Graphs Using Spectrum Feature Vectors in a SOM Network

Finding Patterns in Labeled Graphs Using Spectrum Feature Ve...

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International Joint Conference on Neural Networks (IJCNN)

作者： Fonseca, Rigoberto Gomez-Gil, Pilar Gonzalez, Jesus A. Olmos, Ivan Natl Inst Astrophys Opt & Elect Tonantzintla Mexico Benemerita Univ Autonoma Puebla Puebla Mexico

ISBN: (纸本)9781424496365

Knowledge discovery in structured databases is very important nowadays. In the last years, graph-based data mining algorithms have used artificial neural networks as tools to support clustering. Several of these algorithms have obtained promising results, but they show expensive computational costs. In this work we introduce an algorithm for clustering graphs based on a SOM network, which is part of a process for discovering useful frequent patterns in large graph databases. Our algorithm is able to handle non-directed, cyclic graphs with labels in vertices and edges. An important characteristic is that it presents polynomial computational complexity, because it uses as input a feature vector built with the spectra of the Laplacian of an adjacent matrix. Such matrix contains codes representing the labels in the graph, which preserves the semantic information included in the graphs to be grouped. We tested our algorithm in a small set of graphs and in a large structured database, finding that it creates meaningful groups of graphs.

关键词： Algorithm design and analysis Clustering algorithms complexity theory Databases Laplace equations Neurons SOM network Training adjacent matrix artificial neural networks computational complexity data mining feature vector graph clustering graph theory graph-based data mining algorithms knowledge discovery labeled graphs matrix algebra nondirected cyclic graphs pattern clustering polynomial computational complexity polynomials self-organising feature maps self-organizing map spectrum feature vectors structured databases

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Direct algorithms to solve the two-sided obstacle problem for an M-matrix

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NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS 2006年第7期13卷 543-551页

作者： Zeng, J. P. Jiang, Y. J. Hunan Univ Coll Math & Econometr Changsha 410082 Hunan Peoples R China Changsha Univ Sci & Technol Coll Math & Comp Sci Changsha Peoples R China Hunan Univ State Key Lab Adv Design & Mfg Vehicle Body Changsha Peoples R China

In this paper, two direct algorithms for solving the two-sided obstacle problem with an M-matrix are presented. The algorithms are well defined and have polynomial computational complexity. Copyright (C) 2006 John Wil... 详细信息

关键词： two-sided obstacle problem direct algorithm M-matrix polynomial computational complexity

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