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A collaborative optimization design method of platform location and well trajectory for a complex-structure well factory 认领 引用
1
作者 WANG Ge GAO Deli HUANG Wenjun 《Petroleum Exploration and Development》 SCIE 2026年第1期261-271,共11页
Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drill... Using platform-target matching deviation,anti-collision difficulty,trajectory complexity,and total drilling footage as objective functions,and comprehensively considering constraints such as platform layout area,drilling extension limits,underground target distribution and trajectory collision risks,a model of platform location-wellbore trajectory collaborative optimization for a complex-structure well factory is developed.A hybrid heuristic algorithm is proposed by combining an improved sparrow search algorithm(ISSA)for optimizing platform parameters in the outer layer and a directed artificial bee colony algorithm(DABC)for optimizing trajectory parameters in the inner layer.The alternating iteration of ISSA-DABC facilitates the resolution of the collaborative optimization problem.The ISSA-DABC provides an effective solution to the platform-trajectory collaborative optimization problem for complex-structure well factories and overcomes the tendency of the traditional platform-trajectory stepwise optimization workflow to become trapped in local optima and yield inconsistent designs.The ISSA-DABC has a strong global search capability,fast convergence and good robustness,and can simultaneously satisfy multiple engineering constraints on drilling footage,trajectory complexity and collision risk,and enables automated,workflow-wide generation of constraint-compliant,near-globally optimal platform-trajectory configurations.Field applications further demonstrate that ISSA-DABC significantly reduces the objective function value and collision risk,yielding more rational platform layouts and well factory design parameters. 展开更多
关键词 complex-structure well factory ISSA DABC platform-trajectory collaborative optimization well factory parameter optimization
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Research on Collaborative Optimization Strategies of New Energy Storage Technologies in Clean Energy Grid Integration 认领 引用
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作者 CHEN Yong ZHANG Jiazhi 《外文科技期刊数据库（文摘版）工程技术》 2026年第1期062-066,共5页
With the growing global demand for clean energy, the grid integration of clean energy faces numerous challenges, and new energy storage technologies have become the key to solving these problems. This paper conducts a... With the growing global demand for clean energy, the grid integration of clean energy faces numerous challenges, and new energy storage technologies have become the key to solving these problems. This paper conducts an in‑depth study on the collaborative optimization strategies of new energy storage technologies in clean energy grid integration, analyzes the characteristics of various new energy storage technologies in detail, discusses their application status and challenges in clean energy grid integration, constructs a collaborative optimization model, and proposes corresponding optimization strategies. The research shows that the rational application of new energy storage technologies and the implementation of collaborative optimization strategies can significantly improve the stability, reliability and economy of clean energy grid integration, providing strong support for promoting the green transformation of energy. 展开更多
关键词 new energy storage technologies clean energy grid integration collaborative optimization stability economy
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Research on Differentiated Characteristics and Collaborative Optimization of Child-Friendly Facility Demands in Parent-Child Tourism in Chongqing 认领 引用
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作者 Qi Huang 《Proceedings of Business and Economic Studies》 2026年第6期82-94,共13页
Driven by demographic structural changes and an upgrade in quality consumption,the parent-child tourism market is transitioning from extensive supply to refined services.Child-friendly facilities are key carriers for ... Driven by demographic structural changes and an upgrade in quality consumption,the parent-child tourism market is transitioning from extensive supply to refined services.Child-friendly facilities are key carriers for enhancing the parent-child tourism experience,with their demands showing significant differentiation across various family structures.Existing research often treats“families”as homogeneous entities,overlooking the demand variations arising from differences in family structures.This study takes Chongqing,a mountain city,as a case study,focusing on four types of families:those with multiple children,intergenerational combinations,single-parent families,and dual-income core families.It employs a mixed-methods approach to reveal the differentiated patterns of demand for child-friendly facilities,identifying four core issues such as supply-demand mismatch and inadequate terrain adaptation.Based on these findings,optimization paths are proposed from four dimensions,including facility layout and service design,providing practical guidance for the high-quality development of parent-child tourism in Chongqing and similar mountainous cities. 展开更多
关键词 Parent-child tourism Child-friendly facilities Demand differentiation Collaborative optimization
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Fast-zoom and high-resolution sparse compound-eye camera based on dual-end collaborative optimization 认领 引用 被引量：4
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作者 Yi Zheng Hao-Ran Zhang +5 位作者 Xiao-Wei Li You-Ran Zhao Zhao-Song Li Ye-Hao Hou Chao Liu Qiong-Hua Wang 《Opto-Electronic Advances》 SCIE EI CAS CSCD 2025年第6期4-15,共12页
Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution... Due to the limitations of spatial bandwidth product and data transmission bandwidth,the field of view,resolution,and imaging speed constrain each other in an optical imaging system.Here,a fast-zoom and high-resolution sparse compound-eye camera(CEC)based on dual-end collaborative optimization is proposed,which provides a cost-effective way to break through the trade-off among the field of view,resolution,and imaging speed.In the optical end,a sparse CEC based on liquid lenses is designed,which can realize large-field-of-view imaging in real time,and fast zooming within 5 ms.In the computational end,a disturbed degradation model driven super-resolution network(DDMDSR-Net)is proposed to deal with complex image degradation issues in actual imaging situations,achieving high-robustness and high-fidelity resolution enhancement.Based on the proposed dual-end collaborative optimization framework,the angular resolution of the CEC can be enhanced from 71.6"to 26.0",which provides a solution to realize high-resolution imaging for array camera dispensing with high optical hardware complexity and data transmission bandwidth.Experiments verify the advantages of the CEC based on dual-end collaborative optimization in high-fidelity reconstruction of real scene images,kilometer-level long-distance detection,and dynamic imaging and precise recognition of targets of interest. 展开更多
关键词 compound-eye camera zoom high resolution collaborative optimization
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Efficient obstacle avoidance planning for multi-robot suspension system based on a collaborative optimization for force and position 认领 引用 被引量：1
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作者 Xiangtang Zhao Zhigang Zhao +2 位作者 Cheng Su Jiadong Meng Hutang Sang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2025年第12期135-154,共20页
To avoid collisions between a suspended object,cables,towing robots,and obstacles in the environment in a multi-robot suspension system,obstacle avoidance planning was studied based on a collaborative optimization met... To avoid collisions between a suspended object,cables,towing robots,and obstacles in the environment in a multi-robot suspension system,obstacle avoidance planning was studied based on a collaborative optimization method for force and position.Based on the analysis of the kinematics and dynamics of the system,the inverse kinematics and inverse dynamics of the system are solved using the least variance method.The obstacle avoidance planning is performed in the solved collisionfree feasible space using the stable dung beetle optimization(SDBO)algorithm,which ensures that the suspended object can move stably to the target point in the workspace.The optimal obstacle avoidance trajectory of the multi-robot suspension system can be accurately determined by using the collaborative optimization method for force and position to plan the towing robot and the cable.Finally,the correctness of the obstacle avoidance planning method is verified by simulations.By taking a special scenario,the remarkable findings reveal that the SDBO algorithm outperforms the dung beetle optimization algorithm by reducing the length of the planned trajectory of the suspended object by 14.51%and the height by 79.88%,and reducing the minimum fitness by 95.84%and the average fitness by 94.77%.The results can help the multi-robot suspension system to perform various towing tasks safely and stably,and extend the related planning and control theory. 展开更多
关键词 Suspension system Obstacle avoidance planning Collision-free feasible space Stable dung beetle optimization Collaborative optimization for force and position
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AI-Driven Interaction and Collaborative Optimization of Vehicle,Charging Station and Grid:Challenges and Prospects 认领 引用
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作者 Bo Yang Zhe Jiang +3 位作者 Jianfeng Wen Ning Yang Kaiping Qu Shuai Zhou 《Energy Engineering》 EI 2025年第6期2187-2195,共9页
1 Introduction Amid escalating global climate change,the“dual carbon”goals of carbon peak and carbon neutrality have become a focal point of global attention and an important strategy for sustainable development[1].... 1 Introduction Amid escalating global climate change,the“dual carbon”goals of carbon peak and carbon neutrality have become a focal point of global attention and an important strategy for sustainable development[1].With the rapid development of renewable energy technologies and the increasing public demand for environmental protection and low-carbon living,the adoption of new energy vehicles,particularly electric vehicles(EVs). 展开更多
关键词 Vehicle-to-grid(V2G)interaction artificial intelligence collaborative optimization electric vehicles grid scheduling
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Bi-Level Collaborative Optimization of Electricity-Carbon Integrated Demand Response for Energy-Intensive Industries under Source-Load Interaction 认领 引用
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作者 Huaihu Wang Wen Chen +5 位作者 Jin Yang Rui Su Jiale Li Liao Yuan Zhaobin Du Yujie Meng 《Energy Engineering》 EI 2025年第9期3867-3890,共24页
Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon ... Traditional demand response(DR)programs for energy-intensive industries(EIIs)primarily rely on electricity price signals and often overlook carbon emission factors,limiting their effectiveness in supporting lowcarbon transitions.To address this challenge,this paper proposes an electricity–carbon integratedDR strategy based on a bi-level collaborative optimization framework that coordinates the interaction between the grid and EIIs.At the upper level,the grid operatorminimizes generation and curtailment costs by optimizing unit commitment while determining real-time electricity prices and dynamic carbon emission factors.At the lower level,EIIs respond to these dual signals by minimizing their combined electricity and carbon trading costs,considering their participation in medium-and long-term electricity markets,day-ahead spot markets,and carbon emissions trading schemes.The model accounts for direct and indirect carbon emissions,distributed photovoltaic(PV)generation,and battery energy storage systems.This interaction is structured as a Stackelberg game,where the grid acts as the leader and EIIs as followers,enabling dynamic feedback between pricing signals and load response.Simulation studies on an improved IEEE 30-bus system,with a cement plant as a representative user form EIIs,show that the proposed strategy reduces user-side carbon emissions by 7.95% and grid-side generation cost by 4.66%,though the user’s energy cost increases by 7.80% due to carbon trading.Theresults confirmthat the joint guidance of electricity and carbon prices effectively reshapes user load profiles,encourages peak shaving,and improves PV utilization.This coordinated approach not only achieves emission reduction and cost efficiency but also offers a theoretical and practical foundation for integrating carbon pricing into demand-side energy management in future low-carbon power systems. 展开更多
关键词 Carbon-aware demand response bi-level collaborative optimization dynamic carbon emission factor industrial flexible loads
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Collaborative optimization of maintenance and spare ordering of continuously degrading systems 认领 引用 被引量：6
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作者 Wei Zhou Dongfeng Wang +1 位作者 Jingyu Sheng Bo Guo 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第1期63-70,共8页
A collaborative optimization model for maintenance and spare ordering of a single-unit degrading system is proposed in this paper based on the continuous detection. A gamma distribution is used to model the material d... A collaborative optimization model for maintenance and spare ordering of a single-unit degrading system is proposed in this paper based on the continuous detection. A gamma distribution is used to model the material degradation. The degrading decrement after the imperfect maintenance action is assumed as a random variable normal distribution. This model aims to ob- tain the optimal maintenance policy and spare ordering point with the expected cost rate within system lifecycle as the optimization objective. The rationality and feasibility of the model are proved through a numerical example. 展开更多
关键词 collaborative optimization maintenance spare order- ing degrading system.
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Bilateral Collaborative Optimization for Cloud Manufacturing Service 认领 引用 被引量：2
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作者 Bin Xu Yong Tang +3 位作者 Yi Zhu Wenqing Yan Cheng He Jin Qi 《Computers, Materials & Continua》 SCIE EI 2020年第9期2031-2042,共12页
Manufacturing service composition of the supply side and scheduling of the demand side are two important components of Cloud Manufacturing,which directly affect the quality of Cloud Manufacturing services.However,the ... Manufacturing service composition of the supply side and scheduling of the demand side are two important components of Cloud Manufacturing,which directly affect the quality of Cloud Manufacturing services.However,the previous studies on the two components are carried out independently and thus ignoring the internal relations and mutual constraints.Considering the two components on both sides of the supply and the demand of Cloud Manufacturing services at the same time,a Bilateral Collaborative Optimization Model of Cloud Manufacturing(BCOM-CMfg)is constructed in this paper.In BCOM-CMfg,to solve the manufacturing service scheduling problem on the supply side,a new efficient manufacturing service scheduling strategy is proposed.Then,as the input of the service composition problem on the demand side,the scheduling strategy is used to build the BCOM-CMfg.Furthermore,the Cooperation Level(CPL)between services is added as an evaluation index in BCOM-CMfg,which reveals the importance of the relationship between services.To improve the quality of manufacturing services more comprehensively.Finally,a Self-adaptive Multi-objective Pigeon-inspired Optimization algorithm(S-MOPIO)is proposed to solve the BCOM-CMfg.Simulation results show that the BCOM-CMfg model has advantages in reliability and cost and S-MOPIO can solve BCOM-CMfg effectively. 展开更多
关键词 Service composition service scheduling bilateral collaborative optimization evolutionary computation PIO
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Application of the Improved Collaborative Optimization on Ships’Conceptual Design 认领 引用 被引量：5
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作者 YAO Zhuang-le CHEN Chao-he 《船舶力学》 EI CSCD 北大核心 2014年第12期1453-1459,共7页
The development of multidisciplinary design optimization method and its broad application prospects in ship design are presented.The collaborative optimization is described in detail.According to its disadvantage,a dy... The development of multidisciplinary design optimization method and its broad application prospects in ship design are presented.The collaborative optimization is described in detail.According to its disadvantage,a dynamic penalty function method is proposed.It is based on the modification of the system level optimization problem,and is turned into an unconstrained optimization problems.It can reduce the difficulties and improve the calculation accuracy.A resistance and structural optimization problem of certain SWATH is simplified and solved,and the final result lowers fuel consumption,and shows that this algorithm application in ship's conceptual design is feasible. 展开更多
关键词 collaborative optimization dynamic penalty function small waterplane area twin-hulls ship(SWATH)
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Improvement of Collaborative Optimization 认领 引用 被引量：3
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作者 黄海燕 王德禹 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第2期172-177,共6页
This paper presents a new improved collaborative optimization (CO) model that provides solution capabilities for multiobjective multidisciplinary optimization problems. Reasons that cause computational difficulties in... This paper presents a new improved collaborative optimization (CO) model that provides solution capabilities for multiobjective multidisciplinary optimization problems. Reasons that cause computational difficulties in CO algorithm are firstly analyzed. Then a new system level objective function is advised to minimize relative value between the collaborative objective function and single disciplinary objective function. And it eliminates the effect of dimensions and magnitude orders among objectives. A new subsystem level objective function is developed that includes the disciplinary objective function and the consistency constraint. A new CO framework which is more suitable for multilevel distributed design is advised. In this CO framework,the system level optimizer does not only independently invoke the subdisciplinary analysis tools,but also invoke its subdiscipline optimizer. The improved CO model proposed in this work is demonstrated with two examples. The results of examples show the improved CO is not only feasible,reliable and efficient,but also well suitable to solve the multiobjective optimization problems in multidisciplinary design environment. 展开更多
关键词 multidisciplinary design optimization collaborative optimization (CO) multiobjective improvement
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Damping Collaborative Optimization of Five-suspensions for Driver-seat-cab Coupled System 认领 引用 被引量：4
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作者 ZHAO Leilei ZHOU Changcheng YU Yuewei 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2016年第4期773-780,共8页
Both the seat and cab system of truck play a vital role in ride comfort.The damping matching methods of the two systems are studied separately at present.However,the driver,seat,and cab system are one inseparable whol... Both the seat and cab system of truck play a vital role in ride comfort.The damping matching methods of the two systems are studied separately at present.However,the driver,seat,and cab system are one inseparable whole.In order to further improve ride comfort,the seat suspension is regarded as the fifth suspension of the cab,a new idea of ＂Five-suspensions＂ is proposed.Based on this idea,a 4 degree-of-freedom driver-seat-cab coupled system model is presented.Using the tested cab suspensions excitations as inputs and seat acceleration response as compared output,the simulation model is built.Taking optimal ride comfort as target,a new method of damping collaborative optimization for Five-suspensions is proposed.With a practical example of seat and cab system,the damping parameters are optimized and validated by simulation and bench test.The results show the seat vertical frequency-weighted RMS acceleration values tested for the un-optimized and optimized Five-suspensions are 0.50 m/s～2 and 0.39 m/s～2,respectively,with a decrease by 22.0%,which proves the model and method proposed are correct and reliable.The idea of ＂Five-suspensions＂ and the method proposed provide a reference for achieving global optimal damping matching of seat suspension and cab suspensions. 展开更多
关键词 vehicle engineering seat and cab system Five-suspensions damping collaborative optimization
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Design of hydraulic shift mechanism for AMT vehicles based on the collaborative optimization method 认领 引用 被引量：1
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作者 苗成生 刘海鸥 +1 位作者 陈慧岩 胡宇辉 《Journal of Beijing Institute of Technology》 EI CAS 2016年第1期35-41,共7页
Based on multidisciplinary design optimization（MDO）,a new design method is put forward for hydraulic shift mechanism of heavy-duty vehicle automated manual transmission（AMT）.Taking a shift cylinder for example,the... Based on multidisciplinary design optimization（MDO）,a new design method is put forward for hydraulic shift mechanism of heavy-duty vehicle automated manual transmission（AMT）.Taking a shift cylinder for example,the collaborative optimization（CO）method for the design problem of a cylinder is devided into one system level design optimization problem and three subsystem level design optimization problems.The system level is an economic model and the subsystem level is mechanics,kinetics,and a reliability model.Application of the multidisciplinary design optimization software iSIGHT modeling and solving,optimal solution of the shifting cylinder CO model is obtained.According to the optimal solution,oil cylinders are machined out and installed on the gearbox of an AMT system for the bench cycle shift test.The results show that the output force and action speed of the optimized mechanism can meet requirements very well.In addition,the optimized mechanism has a better performance compared to the structure of the traditional design method,which indicates that the CO method can optimize the design of hydraulic transmission. 展开更多
关键词 hydraulic shifting mechanism collaborative optimization automated manual transmission
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Static and dynamic collaborative optimization of ship hull structure 认领 引用 被引量：7
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作者 黄海燕 王德禹 《Journal of Marine Science and Application》 2009年第1期77-82,共6页
The goal of this effort was to provide a static and dynamic collaborative optimization （CO） model for the design of ship hull structure. The CO model integrated with static, mode and dynamic analyses. In the system-... The goal of this effort was to provide a static and dynamic collaborative optimization （CO） model for the design of ship hull structure. The CO model integrated with static, mode and dynamic analyses. In the system-level optimization model, a new objective function was advised, integrating all the subsystem-levels＇ objective functions, so as to eliminate the effects of dimensions and magnitude order. The proposed CO architecture enabled multi-objectives of the system and subsystem-level to be considered at both levels during optimization. A bi-level optimization strategy was advised, using the multi-island genetic algorithm. The proposed model was demonstrated with a deck optimization problem of container ship stern. The analysis progress and results of example show that the CO strategy is not only feasible and reliable, but also well suited for use in actual optimization problems of ship design. 展开更多
关键词 collaborative optimization multi-island genetic algorithm static analysis dynamic analysis
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Application of the optimal Latin hypercube design and radial basis function network to collaborative optimization 认领 引用 被引量：16
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作者 ZHAO Min CUI Wei-cheng 《Journal of Marine Science and Application》 2007年第3期24-32,共9页
Improving the efficiency of ship optimization is crucial for modem ship design. Compared with traditional methods, multidisciplinary design optimization （MDO） is a more promising approach. For this reason, Collabora... Improving the efficiency of ship optimization is crucial for modem ship design. Compared with traditional methods, multidisciplinary design optimization （MDO） is a more promising approach. For this reason, Collaborative Optimization （CO） is discussed and analyzed in this paper. As one of the most frequently applied MDO methods, CO promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However, there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, optimal Latin hypercube design and Radial basis function network were applied to CO. Optimal Latin hypercube design is a modified Latin Hypercube design. Radial basis function network approximates the optimization model, and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method. 展开更多
关键词 multidisciplinary design optimization （MDO） collaborative optimization （CO） optimal Latin hypercube design radial basis function network approximation
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Collaborative optimization model of renewable energy development considering peak shaving costs of various flexibility resources 认领 引用 被引量：6
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作者 Ji Liang Xingang Zhao Shangdong Yang 《Global Energy Interconnection》 EI CSCD 2021年第4期394-404,共11页
China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of ne... China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of new energies is the limited flexibility of regulations on power system resources,resulting in insufficient consumption capacity.Thus,the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered.In this study,a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system,comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost,and combining renewable energy output characteristics,load forecasting,grid development,and other factors.For the optimization of various flexible resource utilization methods,a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources.A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation,safety,and environmental protection was proposed.Finally,a certain area of Gansu Province was used as an example to perform detailed analysis and calculation,which demonstrated that the model has an optimal effect.This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations. 展开更多
关键词 Renewable Energy Peak Shaving Cost Collaborative Optimization Model
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Force-position collaborative optimization of rope-driven snake manipulator for capturing non-cooperative space targets 认领 引用 被引量：1
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作者 Xiaofeng LI Jian TIAN +1 位作者 Cheng WEI Xibin CAO 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2024年第9期369-384,共16页
With the rapid development of space activities,non-cooperative space targets increase swiftly,such as failed satellites and upper stages,threating normal spacecrafts seriously.As there are some problems in the capture... With the rapid development of space activities,non-cooperative space targets increase swiftly,such as failed satellites and upper stages,threating normal spacecrafts seriously.As there are some problems in the capture process,such as excessive collision and fast tumbling of targets,manipulator with redundant Degrees of Freedom(DOFs)can be used to improve the compliance and therefore solve these problems.The Rope-Driven Snake Manipulator(RDSM)is a combina-tion of hyper-redundant DOFs and better compliance,and therefore it is suitable for capturing mis-sion.In this paper,a snake manipulator mechanism is designed,and the complete kinematic model and system dynamic model considering RDSM,target and contact is established.Then,to obtain the configuration of joint with hyper-redundant DOFs,an improved motion dexterity index is pro-posed as the joint motion optimization target.Besides,the force-position collaborative optimization index is designed to adjust active stiffness,and the impedance control method based on the modified index is used to capture the space target.Finally,the proposed force-position collaborative opti-mization method is verified by virtual prototype co-simulation.The results demonstrate that based on the proposed method,the collision force is reduced by about 25%compared to normal impe-dance control,showing higher safety. 展开更多
关键词 Capturing non-cooperative spacetargets Rope-driven snakemanipu-lator Force-position collaborative optimization Redundant degrees of free-dom Active stiffness adjustment
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Collaborative Optimization of a Matrix Manufacturing System Based on Overall Equipment Effectiveness 认领 引用
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作者 Fengque Pei Jianhua Liu +2 位作者 Cunbo Zhuang Liang Zheng Jiapeng Zhang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第5期113-125,共13页
When several traditional flow-shop lines operate in parallel,the operation mode with no communication between production lines will no longer be the optimal production paradigm.This paper describes matrix manufacturin... When several traditional flow-shop lines operate in parallel,the operation mode with no communication between production lines will no longer be the optimal production paradigm.This paper describes matrix manufacturing systems(MMS)in a general manner from the perspective of related works,comparing different manufacturing organizational forms and their characteristics.Subsequently,MMS are extracted during the parallel production of multiple surface mount technology(SMT)lines.An overall equipment effectiveness(OEE)online calculation model and a collaborative optimization method are proposed based on the OEE of the MMS.The innovative idea of this study is to divide existing multiple parallel SMT lines into MMS.The efficiency of each matrix unit(MU)was calculated,and a collaborative optimization method was proposed based on an indicator(OEE).In this paper,an example of eight SMT lines is presented.The partitioning of MUs,OEE calculation of each MU,and the low OEE unit collaborative optimization method are described in detail.Through a case study,the architecture of the collaborative optimization model for the MMS was constructed and discussed.Finally,the improvement in the OEE proved the effectiveness and usability of the proposed architecture. 展开更多
关键词 Collaborative optimization Matrix production system Overall equipment effectiveness
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Towards a More Resilient and Cost-efficient Fresh Agri-food Supply Chain:A Collaborative Optimization via System Dynamics Methodology 认领 引用
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作者 Cuixia WANG Yilin LIU +2 位作者 Yaqin LI Lisha YUAN Lanzhi LIU 《Journal of Systems Science and Information》 CSCD 2026年第1期92-117,共26页
In recent years,extreme weather events and pest/disease issues have made the resilience of the Agri-food supply chain a focus of social concern.Enterprises typically adopt two primary strategies to enhance the supply ... In recent years,extreme weather events and pest/disease issues have made the resilience of the Agri-food supply chain a focus of social concern.Enterprises typically adopt two primary strategies to enhance the supply chain's resilience,namely maintaining high inventory levels and improving logistics timeliness.The former,particularly through the implementation of the safety stock strategy,appears more feasible in the short term but incurs significant costs,especially for Agri-food.Therefore,striking a balance between resilience and cost efficiency is essential.This paper proposes a system dynamics model to collaboratively optimize resilience and holding costs in a three-level Agri-food supply chain.Using demand fulfillment rate as a resilience indicator,six simulation scenarios with varying inventory and transportation time configurations are designed.The dynamic impacts of these factors on both costs and resilience are analyzed.Optimization is performed using the Powell hill climbing algorithm in Vensim® DSS to adjust the safety stock strategy.Results show that:Reducing distributors'transport time enhances resilience more,but at higher costs;increasing the inventory levels of retailers and distributors is more effective in improving resilience,though also accompanied by increased costs;Collaborative optimization among supply chain members can maximize both resilience and cost efficiency. 展开更多
关键词 fresh Agri-food supply chain resilience holding costs collaborative optimization system dynamics
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Collaborative Quality Management in Industrial Engineering from a Supply Chain Perspective:AI-Driven Enterprise Quality Optimization 认领 引用
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作者 Jiakai Zhong 《Journal of Electronic Research and Application》 2026年第1期43-49,共7页
Amidst the intensifying digital economy and global competition,supply chain quality management is evolving from traditional linear models toward networked systems characterized by data-driven and intelligent collabora... Amidst the intensifying digital economy and global competition,supply chain quality management is evolving from traditional linear models toward networked systems characterized by data-driven and intelligent collaboration.This paper constructs an AI-driven“Supply Chain Quality Collaborative Management”framework through system optimization and artificial intelligence analytical capabilities from a supply chain perspective.The study first analyzes core challenges in supply chain quality collaboration across three dimensions:data fragmentation,standard discrepancies,and mechanism asymmetry.It highlights that traditional static and reactive quality controls struggle to adapt to complex,dynamic supply chain ecosystems.Subsequently,through systematic literature review and theoretical synthesis,the paper elucidates AI’s role in multi-source quality data fusion,semantic alignment,standardized governance,and intelligent incentives.It proposes collaborative optimization pathways based on deep learning,blockchain,and reinforcement learning.Through case studies in the automotive and pharmaceutical industries,the research validates the feasibility of AI in predictive maintenance and cross-linkage collaborative decision-making,demonstrating AI’s ability to significantly enhance the systemic resilience and decision-response capabilities of quality management.This paper innovatively integrates industrial engineering process optimization with cross-organizational governance mechanisms for supply chain quality management,providing a new theoretical framework and practical pathway for intelligent manufacturing and sustainable supply chain development. 展开更多
关键词 Supply chain quality management Industrial engineering Artificial intelligence Quality collaborative optimization Data-driven decision-making
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