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Efficient surrogate-based optimization method and application based on collaborative improvement aggregation strategy

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Kongzhi yu Juece/control and Decision 2025年第6期40卷 1975-1984页

作者： Xiao, Tian-Li Wu, Feng Lin, Cheng-Long School of Management Science and Engineering Anhui University of Technology Ma’anshan243002 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma’anshan243002 China School of Economics and Management Anhui Polytechnic University Wuhu241000 China School of Economics and Management Nanjing University of Science and Technology Nanjing210094 China

To address the problem that greedy characteristics lead to slow convergence and low accuracy problems of surrogate-based optimization solutions in the later stage, a collaborative improvement aggregation strategy is proposed, which is extended to an efficient surrogate-based optimization method for expensive black-box problems. The proposed strategy integrates probability improvement and mean improvement criteria using Chebyshev decomposition and achieves a balance between global exploration and local search capabilities through random weight coefficients. In addition, the differences between surrogate-based optimization and surrogate-assisted optimization methods are analyzed from the perspective of candidate point sets, further exploring the role of randomness in optimization design. The experimental results show that this method can effectively improve the convergence accuracy of the optimized solution in black-box problems. Compared with similar techniques, the proposed method has higher convergence accuracy and stronger robustness of optimized solutions. © 2025 Northeast University. All rights reserved.

关键词： Tabu search

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Effect of New Dual-Credit Policy on Electric Vehicle Diffusion in China

SSRN

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SSRN 2025年

作者： Zhao, Dan Wang, Jian Li, Wen-Wu Huang, Shuai Tang, Jin-Huan School of Management Science and Engineering Anhui University of Technology Ma'anshan243032 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma'anshan243002 China School of Economics and Management Shenyang Aerospace University Shenyang110136 China School of Business Qingdao University Qingdao266071 China

The impact of new dual-credit policy on electric vehicle (EV) diffusion is examined through complex network evolutionary game theory, we find that merely tightening new energy vehicle (NEV) credit rule and corporate average fuel consumption (CAFC) credit rule may not necessarily benefit the growth of auto industry. This paper further discusses the influence of different update strategies on EV diffusion. The results indicate that with the increase of NEV credit accounting coefficient, the upper limit of threshold interval of NEV credit trading price remains unchanged, while lower limit decreases. With the decrease of ratio of standard CAFC to target CAFC or the increase of requirement of NEV credits for fuel vehicle manufacturer, the upper and lower limits of threshold interval of NEV credit price are reduced. With the increasing network scale, the driving effect of Fermi function is gradually superior to EWA algorithm. © 2025, The Authors. All rights reserved.

关键词： Automotive industry

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Multi-criteria consensus sorting model with flexible linguistic preferences based on fuzzy information granulation from the perspective of preference disaggregation

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Engineering Applications of Artificial Intelligence 2025年 154卷

作者： Zhang, Shiji Zhang, Shitao Tian, Hao Deveci, Muhammet Liu, Xiaodi School of Microelectronics and Data Science Anhui University of Technology Ma'anshan243032 China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma'anshan243002 China Anhui Provincial Joint Key Laboratory of Disciplines for Industrial Big Data Analysis and Intelligent Decision Ma'anshan243032 China Department of Industrial Engineering Turkish Naval Academy National Defence University Tuzla Istanbul34942 Turkey The Bartlett School of Sustainable Construction University College London LondonWC1E 6BT United Kingdom Department of Information Technologies Western Caspian University Baku1001 Azerbaijan

Multi-criteria group sorting (MCGS) that considers linguistic preferences involves multiple individuals evaluating alternatives and assigning them to pre-determined ordered categories based on specific criteria. Nevertheless, due to the limited availability of class information and the constrained cognitive capacity of decision-makers (DMs), it becomes challenging for DMs to furnish explicit preference information to reach consensus. Besides, decision parameters such as consensus threshold and class thresholds are also too hard to be assumed in advance. Therefore, this paper studies the preference disaggregation problem in MCGS, in which DMs are allowed to provide their pairwise comparisons in flexible linguistic expressions (FLEs) as preference information. To more fully utilize the preferences, semantic granulation is introduced. First, an individual consistency recognition model is proposed to identify inconsistent preferences and provide modification directions to the corresponding individuals. Next, semantic granulation and maximum entropy are combined into a granulation-driven information transformation model to convert the preference information based on FLEs into triangular fuzzy numbers (TFNs). Subsequently, in the consensus-driven preference disaggregation model, decision parameters and sorting results can be obtained at the premise of consensus by adjusting weights. Ultimately, to substantiate the effectiveness of the proposal, two numerical applications concerning the sorting of government venture capitals and information system suppliers are presented, along with comparative analysis, sensitivity analysis, and simulation analysis. © 2025 The Authors

关键词： Information granules

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An Image Denoising Model via the Reconciliation of the Sparsity and Low-Rankness of the Dictionary Domain Coefficients

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Wuhan University Journal of Natural Sciences 2023年第1期28卷 61-67页

作者： YANG Yifan ZHANG Tao WU Di ZHAO Yu Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMaanshan 243002AnhuiChina School of Mathematics and Physics Anhui University of TechnologyMaanshan 243032AnhuiChina

Sparse coding has achieved great success in various image restoration ***,if the sparse representation coefficients of the structure(low-frequency information)and texture(high-frequency information)components of the image are under the same penalty constraint,the restoration effect may not be *** this paper,an image denoising model combining mixed norm and weighted nuclear norm as regularization terms is *** proposed model simultaneously exploits the group sparsity of the high frequency and lowrankness of the low frequency in *** mixed norm is used to constrain the high frequency part and the weighted nuclear norm is used to constrain the low frequency *** order to make the proposed model easy to solve under the framework of alternative direction multiplier method(ADMM),iterative shrinkage threshold method and weighted nuclear norm minimization method are used to solve the two *** validity of the model is verified experimentally through comparison with some state-of-the-art methods.

关键词： image denoising mixed norm sparse representation principal component analysis(PCA)dictionary

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Non-Blind Image Deblurring Method Using Shear High Order Total Variation Norm

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Wuhan University Journal of Natural Sciences 2021年第6期26卷 495-506页

作者： LU Lixuan ZHANG Tao School of Mathematics and Physics Anhui University of TechnologyMaanshan 243002AnhuiChina Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMaanshan 243002AnhuiChina

In this paper,we propose a shear high-order gradient(SHOG)operator by combining the shear operator and high-order gradient(HOG)*** with the HOG operator,the proposed SHOG operator can incorporate more directionality and detect more abundant edge *** on the SHOG operator,we extend the total variation(TV)norm to shear high-order total variation(SHOTV),and then propose a SHOTV deblurring *** also study some properties of the SHOG operator,and show that the SHOG matrices are Block Circulant with Circulant Blocks(BCCB)when the shear angle isπ/*** proposed model is solved efficiently by the alternating direction method of multipliers(ADMM).Experimental results demonstrate that the proposed method outperforms some state-of-the-art non-blind deblurring methods in both objective and perceptual quality.

关键词： image deblurring high-order TV norm Block Circulant with Circulant Blocks(BCCB)matrix shear operator alternating direction method of multipliers(ADMM)

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Group Sparsity Residual Constraint Image Denoising Model with l_(1)/l_(2)Regularization

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Wuhan University Journal of Natural Sciences 2023年第1期28卷 53-60页

作者： WU Di ZHANG Tao MO Xutao Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMaanshan 243002AnhuiChina School of Mathematics and Physics Anhui University of TechnologyMaanshan 243032AnhuiChina

Group sparse residual constraint with non-local priors(GSRC)has achieved great success in image restoration producing stateof-the-art *** the GSRC model,the l_(1)norm minimization is employed to reduce the group sparse *** recent years,nonconvex regularization terms have been widely used in image denoising problems,which have achieved better results in denoising than convex regularization *** this paper,we use the ratio of the l_(1)and l_(2)norm instead of the l_(1)norm to propose a new image denoising model,i.e.,a group sparse residual constraint model with l_(1)/l_(2)minimization(GSRC-l_(1)/l_(2)).Due to the computational difficulties arisen from the non-convexity and non-linearity,we focus on a constrained optimization problem that can be solved by alternative direction method of multipliers(ADMM).Experimental results of image denoising show that the pro-posed model outperforms several state-of-the-art image denoising methods both visually and quantitatively.

关键词： image denoising l_(1)/l_(2)minimization group sparse representation

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MRO Configuration management for complex Products

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Journal of systems Science and systems Engineering 2022年第3期31卷 359-380页

作者： Chunliu Zhou Lian Qi Xiaobing Liu Hongguang Bo Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMaanshan 243002China School of Management Science and Engineering Anhui University of TechnologyMaanshan 243032China Rutgers Business School RutgersThe State University of New JerseyPiscatawayNJ 08854United State School of Economics and Management Dalian University of TechnologyDalian 116023China

Configuration management(CM)is an effective method for data modeling and change management in product development,but the study of how it can be adapted for complex product maintenance,repair and overhaul(MRO)has thus far been *** propositions are put forward on the basis of a literature review and verified by a case of a high-speed train MRO *** findings show that CM can be used in MRO data management with adjustments in its ***,MRO-CM planning considers both multistage service and single-stage service to keep data consistent and ***,MRO data integration with the design/production phase should be considered during configuration ***,baselines and change rules are developed for change ***,status accounting and auditing can be repeatedly used in MRO data management.A systematic MRO-CM framework is generated to assist MRO practitioners in understanding the relationships among different MRO-CM *** paper contributes to expanding the theory of CM in MRO for complex products and provides an effective method for managing MRO data from systematic engineering insights.

关键词： Configuration management MRO Service data management case study

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Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1459-1483页

作者： Hongliang Zhang Yi Chen Yuteng Zhang Gongjie Xu School of Management Science and Engineering Anhui University of TechnologyMa’anshan243032China Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMa’anshan243032China Department of Industrial Engineering School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an710072China

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing *** DFJSP research only considers machine constraints and ignores worker *** one critical factor of production,effective utilization of worker resources can increase ***,energy consumption is a growing concern due to the increasingly serious environmental ***,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this *** solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling *** further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are *** strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto *** effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 *** results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

关键词： Distributed flexible job shop scheduling problem dual resource constraints energy-saving scheduling multi-objective grey wolf optimizer Q-learning

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Dynamic Maintenance Document management Based on BOM 7

Dynamic Maintenance Document Management Based on BOM

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7th International Conference on systems and Informatics, ICSAI 2021

作者： Zhou, Chunliu Ye, Shan Wang, Hongjun Gao, Zhenhua Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Key Laboratory of Multidisciplinary Management Ma'anshan China School of Management Science and Engineering Anhui University of Technology Ma'anshan China

ISBN: (纸本)9781665426244

To realize the efficient management of high-speed train maintenance documents, a document management method based on the Bill of Material (BOM) was proposed. Since the maintenance documents were dynamically changed as the design updated, and the change process was complicated and time-consuming via handwork, the relationship between the Engineering BOM (EBOM) and the Documental BOM (DBOM) was established, which delivered the design change, updated the maintenance documents in real time, and provided the latest documents for on-site maintenance business. Technologies of fuzzy matching, version management and XML were used together to realized the dynamic management of maintenance documents, and an application was displayed with system interfaces to verify the DBOM method. © 2021 IEEE.

关键词： Maintenance

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Finite-time Robust Fault-tolerant Trajectory Tracking control for QUAVs with Actuator Fault 7

Finite-time Robust Fault-tolerant Trajectory Tracking Contro...

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7th International Conference on Robotics, control and Automation Engineering, RCAE 2024

作者： Xia, Rongsheng Bu, Chunlei Jiang, Han Chery Automobile Stock Limited Company Wuhu241006 China Anhui University of Technology School of Electrical and Information Engineering Ma'Anshan243032 China Anhui University of Technology Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Ma'Anshan243002 China

ISBN: (纸本)9798350355642

This paper proposed a finite-time robust fault-tolerant trajectory tracking control strategy for quadrotor unmanned aerial vehicles (QUAVs) suffering from actuator saturation, unknown external disturbance and actuator fault. Firstly, robust compensation terms are used to handle unknown external disturbance in position subsystem. On this basis, parameter adaptive method is introduced to remove the adverse effects of actuator saturation in attitude subsystem. Then, a fault detection mechanism is designed to estimate the actuator fault in real time. Subsequently, a finite-time robust fault-tolerant tracking strategy based on backstepping framework are proposed and and the finite-time convergence of all error signals are ensurend. Finally, a numerical simulation result is displayed to validate the effectiveness of the proposed trajectory tracking control scheme for the QUAVs dynamic system. © 2024 IEEE.

关键词： Backstepping

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