检索结果-内蒙古大学图书馆

RESOURCE allocation optimization FOR EFFECTIVE VEHICLE NETWORK COMMUNICATIONS USING MULTI-AGENT DEEP REINFORCEMENT LEARNING

引用

JOURNAL OF DYNAMICS AND GAMES 2025年第2期12卷 134-156页

作者： Ergun, Serap Isparta Univ Appl Sci Isparta Turkiye

In the realm of vehicular networks, ensuring top-notch services for high-speed mobile vehicles remains a formidable challenge. This study squarely addresses the spectrum-sharing predicament within the Internet of Vehicles (IoV) by scrutinizing the spectrum shared by V2I links serving multiple V2V links. The swiftness of vehicular movement ushers in challenges for centralized resource management, necessitating an innovative approach. To surmount this obstacle, the resource allocation is casted as a Multi-agent Deep Reinforcement Learning (RL) and a distributed Multi-Agent Deep Deterministic Policy Algorithm (MADDPG) algorithm is introduced. Each agent autonomously interacts with the vehicular network, assessing its local state and receiving a shared reward. Through collaboration, the Critic network refines power control for each agent. The reward function and training mechanism empower the multi-agent algorithm to attain distributed resource allocation, markedly enhancing both V2I link capacity and V2V transmission rates. This pioneering approach optimizes spectrum utilization, ushering in superior service quality for high-speed mobile vehicles in vehicular networks.

关键词： Internet of Vehicles (IoV) vehicular networks spectrum sharing allocation optimization multi-agent deep reinforcement learning wireless networks

来源：评论

学校读者我要写书评

暂无评论

Effects on Optimal Merging Trajectories with allocation optimization from the Trade-off between Fuel Consumption and Flight Time

引用

SICE Journal of Control, Measurement, and System Integration 2018年第3期11卷 182-189页

作者： Daichi Toratani Eri Itoh Air Traffic Management Department Electronic Navigation Research Institute National Institute of Maritime Port and Aviation Technology

This study investigates the effects of the trade-off between fuel consumption and flight time on optimal merging trajectories with allocation optimization. A merging optimization method that simultaneously optimizes arrival trajectories and the sequence of aircraft has the potential to improve future decision support systems for air traffic control. In addition, the merging optimization method is required to optimize allocation of the arrival aircraft to parallel runways because most large-scale airports have parallel runways. The merging optimization method with allocation optimization has been developed in previous studies, but only fuel consumption was minimized. Furthermore, in practice, the total flight time must be minimized, and it is possible that the trade-off between minimizing fuel consumption and flight time affects the optimal solution of the merging trajectory. Numerical simulations are performed to demonstrate the variation of the optimal merging trajectory. In particular, this study focuses on the variation of allocation of aircraft, which is a discrete factor in the merging optimization problem. The simulation results show that the allocation of aircraft can change due to the trade-off between minimizing fuel consumption and flight time. The optimality of the allocation is confirmed by comparing with the simulation results with specified allocation.

关键词： merging optimization allocation optimization hybrid system trade-off air traffic management

来源：评论

学校读者我要写书评

暂无评论

Regional Science and Technology Resource allocation optimization Based on Improved Genetic Algorithm

引用

KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2017年第4期11卷 1972-1986页

作者： Xu, Hao Xing, Lining Huang, Lan Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Zhuhai Coll Dept Comp Sci & TechnolMinist Educ Zhuhai Lab Key Lab Symbol Computat & Knowledge En Zhuhai 519041 Peoples R China Foshan Univ Sch Math & Big Data Foshan 528000 Peoples R China Shanghai Polytechn Univ Coll Engn Shanghai 201209 Peoples R China Natl Univ Def Technol Coll Informat Syst & Management Changsha 410073 Hunan Peoples R China Jilin Univ Minist Educ Changchun 130012 Peoples R China

With the advent of the knowledge economy, science and technology resources have played an important role in economic competition, and their optimal allocation has been regarded as very important across the world. Thus, allocation optimization research for regional science and technology resources is significant for accelerating the reform of regional science and technology systems. Regional science and technology resource allocation optimization is modeled as a double-layer optimization model: the entire system is characterized by top-layer optimization, whereas the subsystems are characterized by bottom-layer optimization. To efficaciously solve this optimization problem, we propose a mixed search method based on the orthogonal genetic algorithm and sensitivity analysis. This novel method adopts the integrated modeling concept with a combination of the knowledge model and heuristic search model, on the basis of the heuristic search model, and simultaneously highlights the effect of the knowledge model. To compare the performance of different methods, five methods and two channels were used to address an application example. Both the optimized results and simulation time of the proposed method outperformed those of the other methods. The application of the proposed method to solve the problem of entire system optimization is feasible, correct, and effective.

关键词： Regional science and technology resource allocation optimization genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Research on optimization Method of Ship Spare Parts allocation Based on Improved Discrete Crow Search Algorithm 6th

Research on Optimization Method of Ship Spare Parts Allocati...

引用

6th Conference on Intelligent Networked Things (CINT)

作者： Li, Yanhui Zhang, Yongquan Chen, Zhimin Luo, Wei Xia, Yuan Zhang, Wei Mei, Jiangnuo Wuhan Univ Technol Sch Mech & Elect Engn Wuhan 430000 Peoples R China China Ship Dev & Design Ctr Wuhan Peoples R China

ISBN: (纸本)9789819739479;9789819739486

As the main component of maintenance support resources, how to allocate ship spare parts efficiently and reasonably has always been a key research topic. Aiming at the problem that the allocation of ship spare parts is unreasonable and the demand for some spare parts can not be guaranteed in time, the focus of this paper is the optimization of ship spare parts allocation during the execution of tasks. To achieve this goal, we propose a novel optimization approach for spare parts allocation, drawing inspiration from the improved crow search algorithm. Firstly, Monte Carlo simulation is used to determine the initial scheme of spare parts allocation. Then, the limitation of spare parts allocation and the requirement of ship support department are considered comprehensively. Moreover, an optimization model of inventory allocation under multi-constraints is established. The improved discrete crow search algorithm integrating multiple strategies is used to solve the model to determine the optimal optimization scheme for spare parts. Finally, the accuracy and feasibility of the established model are verified by the actual data of ship spare parts, which can provide

关键词： Ship spare parts Monte Carlo simulation allocation optimization Improved discrete crow search algorithm

来源：评论

学校读者我要写书评

暂无评论

allocation optimization of bicycle-sharing stations at scenic spots

引用

Journal of Central South University 2014年第8期21卷 3396-3403页

作者：郭唐仪张平邵飞刘英舜 School of Automation Nanjing University of Science & Technology Department of Scientific Research PLA University of Science and Technology Engineering Institute PLA University of Science and Technology

Bicycle-sharing system is considered as a green option to provide a better connection between scenic spots and nearby metro/bus stations. Allocating and optimizing the layout of bicycle-sharing system inside the scenic spot and around its influencing area are focused on. It is found that the terrain, land use, nearby transport network and scenery point distribution have significant impact on the allocation of bicycle-sharing system. While the candidate bicycle-sharing stations installed at the inner scenic points, entrances/exits and metro stations are fixed, the ones installed at bus-stations and other passenger concentration buildings are adjustable. Aiming at minimizing the total cycling distance and overlapping rate, an optimization model is proposed and solved based on the idea of cluster concept and greedy heuristic. A revealed preference/stated preference （RP/SP） combined survey was conducted at Xuanwu Lake in Nanjing, China, to get an insight into the touring trip characteristics and bicycle-sharing tendency. The results reveal that 39.81% visitors accept a cycling distance of 1-3 km and 62.50% respondents think that the bicycle-sharing system should charge an appropriate fee. The sttrvey indicates that there is high possibility to carry out a bicycle-sharing system at Xuanwu Lake. Optimizing the allocation problem cluster by cluster rather than using an exhaustive search method significantly reduces the computing amount from O（2^43） to O（43 2）. The 500 m-radius-coverage rate for the alternative optimized by 500 m-radius-cluster and 800 m-radius-cluster is 89.2% and 68.5%, respectively. The final layout scheme will provide decision makers engineering guidelines and theoretical support.

关键词： bicycle-sharing allocation optimization scenic spot cluster

来源：评论

学校读者我要写书评

暂无评论

Research on allocation optimization for Power Quality Monitors in Smart Distribution Grid

Research on Allocation Optimization for Power Quality Monito...

引用

International Conference on Power System Technology (PowerCon)

作者： Xie, Zhiyun Yu, Ziwen Weng, Guoqing Wang, Qiang Zhejiang Univ Technol Coll Informat Engn Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781479950324

This paper summarizes the optimization methods of allocation optimization of power quality monitors (PQM) in the networked power quality monitoring system (NPQMS) and divides them into three categories. Utilizing one of them that takes the system average ambiguity (SAA) as valuation basis and considers some important factors, such as network topology analysis, weighting factor calculation and state estimation for no monitoring nodes, a new automatic locating method for power quality disturbance source (PQDS) in the NPQMS is presented with the definition of virtual PQM and extended matrix algorithm. A case study demonstrated the effectiveness of the proposed method.

关键词： allocation optimization networking power quality monitoring system virtual power quality monitors automatic locating power quality disturbance source

来源：评论

学校读者我要写书评

暂无评论

Statistical analysis for estimating the optimized battery capacity for roof-top PV energy system

引用

RENEWABLE ENERGY 2025年 242卷

作者： Zhang, Yuhang Zhang, Yi Zheng, Bo Cui, Hongzhi Qi, He Tsinghua Univ Inst Future Human Habitats Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Tsinghua Univ Inst Environm & Ecol Tsinghua Shenzhen Int Grad Sch Shenzhen Key Lab Ecol Remediat & Carbon Sequestrat Shenzhen 518055 Peoples R China Shenzhen Univ Coll Civil & Transportat Engn State Key Lab Subtrop Bldg & Urban Sci Shenzhen 518060 Guangdong Peoples R China China Construct Sci & Technol Grp Cooperat 2007 Pingshan Ave Shenzhen 518118 Peoples R China

Calculating optimized battery capacity for building rooftop photovoltaic (PV) consumption efficiently can benefit to decision making and policy implementation. optimization for battery calculation requires speciality, but optimized battery capacities can be fitted based on similarities between buildings. This study aims to proposed a two-stage battery allocation model to efficiently estimate battery capacity for building PV consumption. An integer linear programming model has been constructed in the first stage to allocate battery for buildings. After optimizing part of buildings' battery capacities, quadratic polynomial regression analysis has been applied in the second stage to estimate optimized battery capacity using building information for the rest of buildings. Current scenario with electricity feed-in tariff, future scenario without feed-in tariff and baseline scenario have been considered for scenario analysis to compare method performance. 53,016 buildings in Pingshan district, Shenzhen, China have been used as a case study. For current and future scenarios, optimized battery capacity can be fitted by floor number and building area, the R2 score is higher than 0.94. Compared with current scenario, future scenario increases 5.81 % optimized battery capacity and 2.58 % annual cost. The proposed method can reduce nearly 100 % computation time with only 3.3 % accuracy loss compared with optimization method.

关键词： Battery capacity estimation Roof-top PV energy system allocation optimization Statistical estimation regression

来源：评论

学校读者我要写书评

暂无评论

Optimal resource allocation in common bus performance sharing systems with transmission loss

引用

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2024年第7期40卷 3675-3690页

作者： Gu, Liudong Wang, Guanjun Zhou, Yifan Southeast Univ Sch Math Nanjing 210096 Peoples R China Southeast Univ Sch Mech Engn Nanjing Peoples R China

The reliability modeling and optimization of performance sharing systems (PSSs) are of vital importance due to their wide applications. Existing research mainly focuses on evaluating and maximizing the reliability of PSSs. However, in many practical systems, decision-makers tend to prioritize the average cost of the system over its reliability. This paper studies the resource allocation optimization in common bus PSSs. In such systems, each unit has binary-state random performance to satisfy the multi-state random demand. The surplus performance can be shared via a common bus with transmission loss between the common bus and the unit. The performance allocation, performance transmission, and unsupplied demand incur costs. Resource allocation strategies are determined by optimization models considering different objective functions and constraints. Additionally, transmission loss between the common bus and the unit is considered. A genetic algorithm is employed to efficiently find the optimal allocation strategies. Numerical examples prove the effectiveness of the proposed models in improving system reliability and reducing system costs.

关键词： allocation optimization common bus multi-state systems performance sharing mechanism reliability

来源：评论

学校读者我要写书评

暂无评论

A Survey of Machine Learning Innovations in Ambulance Services: allocation, Routing, and Demand Estimation

IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS

引用

IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS 2024年 5卷 842-872页

作者： Tluli, Reem Badawy, Ahmed Salem, Saeed Barhamgi, Mahmoud Mohamed, Amr Qatar Univ Comp Sci & Engn Dept Doha Qatar

In the realm of Emergency Medical Services (EMS), the integration of Machine Learning (ML) techniques has emerged as a catalyst for revolutionizing ambulance operations. ML algorithms could play a pivotal role in dynamically allocating resources, devising efficient routes, and predicting demand patterns. By thoroughly reviewing the existing literature and methodologies, this paper provides a comprehensive overview of the approaches used in ambulance allocation, routing, demand estimation and simulation models. We discuss the challenges faced by these methods, emphasizing the need for innovative solutions that can adapt to real-time data and changing emergency patterns. Through this survey, we aim to offer valuable insights into the current state of research and practices, shedding light on potential areas for future exploration and development. The findings presented in this paper serve as a foundation for researchers and practitioners working towards enhancing the efficiency of ambulance deployment in EMS.

关键词： Medical services Surveys Routing Resource management Time factors Machine learning Emergency services Prediction algorithms Real-time systems Technological innovation Emergency medical services (EMS) ambulance services machine learning (ml) allocation optimization vehicle routing strategies demand estimation

来源：评论

学校读者我要写书评

暂无评论

Risk Assessment and Management Method of Urban Flood Disaster

引用

WATER RESOURCES MANAGEMENT 2023年第5期37卷 2001-2018页

作者： Li, Jiake Gao, Jiayu Li, Ning Yao, Yutong Jiang, Yishuo Xian Univ Technol State Key Lab Ecohydraul Northwest Arid Reg China Xian 710048 Peoples R China Summit Technol Co Xian 710075 Peoples R China

Due to the failure of flood control and drainage infrastructure to match the rapidly growing urbanization process, urban flooding has become one of the most significant disasters faced today. It is essential to carry out the risk assessment of flood scientifically and study the optimal allocation of stormwater infrastructure in-depth. In this paper, a complete urban flooding risk assessment and management methodology is proposed by linking "scenario simulation", "risk assessment" and "allocation optimization", which is applied in Xiaozhai area of Xi'an, China. Based on the measured data and the results of the maximum water depth survey, an accurate coupled model of flooding in the study area was established, which was used to simulate the current situation and design scenarios. On the basis of the "hazard-vulnerability" framework, a multi-factor flood risk levels were assessed, and four risk gradations were mapped. Taking the results of risk analysis as the point of view, the allocation-effect functions are fitted by the polynomial curves and consisted as a part of objective function. Then, the optimal scenario is obtained by NSGA-III. The results show that the urban flood risk zoning is accurately screened, and the optimal scenario increases the runoff control rate from 54 to 85% compared with the traditional development scenario. The regional risk-free area doubles, the low-risk and medium-risk areas are reduced by a factor of 2 and 16, and the high-risk are all eliminated, with significant flood control effects. The cost savings are 127 million CNY compared to the initial scenario without optimization. The overall idea starts from flood formation, which provides a research method that can be applied to regions with similar problems.

关键词： Flooding disaster MIKE FLOOD Risk assessment allocation optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：