检索结果-内蒙古大学图书馆

Complex Systems and Intelligent Science (CSIS-IAC), International Annual Conference on

作者： Xilin Zhang Shenshen Gu School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

Solving combinatorial optimization problems holds significant practical importance, and many such problems can be transformed into MILP problems. Currently, Branch-and-Bound (B&B) is a typical method for solving mixed-integer linear programming (MILP) problems. In this paper, we propose a hybrid convolutional and attentional graph neural network to learn the variable selection policy in B&B. The model combines graph convolutional and graph attention mechanisms, achieving more efficient node embeddings and reducing computational time. The mathematical model of MILP is transformed into a bipartite graph structure, which effectively extracts features. The B&B solving process is mapped to a Markov decision process, and imitation learning is used to train the model. By solving a series of combinatorial optimization problems that can be transformed into MILP problems, we validate that our model can improve B&B. Experimental results show that our model outperforms state-of-the-art branching machine learning methods and generalizes to problems of different scales.

关键词： Training Imitation learning Computational modeling Predictive models Feature extraction Graph neural networks Mathematical models Bipartite graph mixed integer linear programming Optimization

来源：评论

学校读者我要写书评

暂无评论

Optimizing the inventory and routing decisions in a bike-sharing system: A linear programming and stochastic approach

引用

CASE STUDIES ON TRANSPORT POLICY 2021年第4期9卷 1495-1502页

作者： Possani, Edgar Castillo, Esteban ITAM Inst Tecnol Autonomo Mexico Dept Math Rio Hondo 1 Mexico City 01080 DF Mexico

We evaluate a model to optimize the bicycle inventory logistic of the Mexico City bike-sharing system, Ecobici. A satisfaction function for a given inventory level is defined in terms of the probability of finding available bicycles to take out, and the number of vacant lockers to return them. We estimate this function with real data for each station. Later we linearize this objective function and propose a mixed integer linear programming model that optimizes the inventory policy (removal or deposit) of bicycles at each station as well as the routing of the vehicle within a time limit to minimize a weighted sum of the travel time and the sum of satisfactions over all stations. We present results of the model and compare it with the performance of the system on a particular day. We find that the application of the model may improve the customer satisfaction with the system.

关键词： Inventory management Routing mixed integer linear programming Bike-sharing system

来源：评论

学校读者我要写书评

暂无评论

Optimization of collaborative delivery routes for electric trucks and drones with integrated recharging strategies

Optimization of collaborative delivery routes for electric t...

引用

IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific)

作者： Shu Wang Yimeng Cheng Tian Guan Liming Ma Yi Han The School of Automobile Chang’an University Xi’an China

ISBN: (数字)9798331529277

ISBN: (纸本)9798331529307

With the rapid expansion of global e-commerce, the logistics industry faces increasing demand for last-mile delivery solutions, highlighting the need for sustainable solutions such as the integration of Electric Trucks (ETs) and drones to improve the delivery operational efficiency and reduce the environmental impact. This paper presents a novel routing model to optimize the delivery routes by considering the collaboration of ETs and drones. In response to the problem of limited driving range due to battery capacity constraints in large-scale delivery scenarios, our approach considers the battery limitations of both ETs and drones, allowing ETs to make multiple trips and recharge at designated charging stations, while drones can be recharged by returning to corresponding ETs during the deliveries. Finally, a practical case study based on real-word logistics scenario in Las Vegas is conducted to evaluate the performance of the proposed model, demonstrating significant cost savings and increased delivery efficiency when ETs and drones are allowed to recharge during the delivery process, providing a robust solution for sustainable and efficient large-scale logistics distribution

关键词： Costs Collaboration Transportation Charging stations Routing Batteries mixed integer linear programming Optimization Drones Logistics

来源：评论

学校读者我要写书评

暂无评论

Defense Strategies for Integrated Energy Cyber Physical Systems Considering Joint Attacks

Defense Strategies for Integrated Energy Cyber Physical Syst...

引用

Energy, Electrical and Power Engineering (CEEPE), International Conference on

作者： Danyan Gu Lucheng Hong Qiangqiang Yu Liang Hua College of Software Southeast University Nanjing China College of Electrical Engineering Southeast University Nanjing China State Grid Wuxi Power Supply Company Science and Technology Digital Department Wuxi Power Supply Company Wuxi China

ISBN: (数字)9798350375794

ISBN: (纸本)9798350375800

In the context of a highly interconnected energy landscape, coordinated cyber-physical attacks on integrated energy systems can cause significant damage and trigger considerable economic impacts. In order to ensure the robustness and uninterrupted function of such systems, the interaction between information and physical matrix is analyzed based on the inherent coupling mechanism unique to the integrated energy information-physical framework. After the basic analysis, a threelayer dynamic game model is designed using the strategy of game theory. The model is transformed into a mixed integer linear programming formula, load loss is selected as the vulnerability assessment index, and defense resources are effectively allocated to each component of the integrated energy system. Finally, an IEEE-39-node grid is coupled to an 11-node gas distribution network. Research and analysis, the proposed model and its related methods have been verified.

关键词： Economics Analytical models Power engineering Games Distribution networks Robustness mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Research on Production Decision Optimization Based on Multiple Intelligent Algorithms

Research on Production Decision Optimization Based on Multip...

引用

Electrical, Automation and Computer Engineering (ICEACE), International Conference on

作者： Wengang Qin Yehao Huang Jianye Shang Shanghai Institute of Technology Shanghai China

ISBN: (数字)9798350368208

ISBN: (纸本)9798350368215

This paper investigates the production decision optimization model based on multi-algorithm, using genetic algorithm, particle swarm optimization algorithm and reinforcement learning algorithm, aiming at comparing the optimal algorithm. This study is aimed at an electronic product manufacturing enterprise, which involves the procurement of spare parts, assembly and finished product testing and other aspects. First, a sampling inspection model is constructed to ensure that the defective rate of spare parts does not exceed the nominal value, and the rejection domains at 95% and 90% confidence levels are calculated. Subsequently, an optimization model that comprehensively considers the inspection cost, defective rate, assembly cost, exchange loss and disassembly cost is established for the decision-making of inspection and non-conforming product handling in the production process. Genetic algorithm, particle swarm optimization algorithm and reinforcement learning algorithm are used for comparative analysis, and the results show that the particle swarm algorithm performs optimally in specific contexts, while reinforcement learning is suitable for long-term optimization strategies. In addition, the uncertainty caused by sampling detection is further dealt with by introducing the robust optimization method. Finally, a mixed integer linear programming (MILP) model is constructed to verify its effectiveness in real production decisions. The research in this paper provides scientific decision support for production and manufacturing enterprises, which is of great significance for improving production efficiency and reducing costs.

关键词： Costs Uncertainty Optimization models Production Reinforcement learning Inspection mixed integer linear programming Particle swarm optimization Assembly Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Temporal and spatial coordinated optimization of integrated energy systems under uncertain conditions

Temporal and spatial coordinated optimization of integrated ...

引用

Intelligent Power and Systems (ICIPS), International Conference on

作者： Xiaoxin Zhang Yuguo Lu School of Internet of Things Engineering Jiangnan University Wuxi P.R. China School of Management Anhui Technical College of Mechanical and Electrical Engineering Wuhu P.R. China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

This paper adopts a min-max-min two-layer robust optimization method to deal with the inherent uncertainty of renewable energy power generation units in integrated energy systems. First, the principles of wind power and photovoltaic power generation are analyzed to point out the sources of uncertainty. Then, the uncertainty set of renewable energy power generation is constructed, and the model affected by uncertainty is divided into two layers of models, inner and outer. On this basis, the dual method is used to transform the initial two-layer model into a mixed integer linear programming, and finally the C&CG method is used for iterative solution. Finally, the analysis is carried out on the matlab platform in the form of an example, and the impact of different uncertain parameters on the system economy is discussed.

关键词： Renewable energy sources Uncertainty Costs Optimization methods Transforms Wind power generation Mathematical models mixed integer linear programming Safety Reliability

来源：评论

学校读者我要写书评

暂无评论

Learning Optimal Signal Temporal Logic Decision Trees for Classification: A Max-Flow MILP Formulation

Learning Optimal Signal Temporal Logic Decision Trees for Cl...

引用

IEEE Conference on Decision and Control

作者： Kaier Liang Gustavo A. Cardona Disha Kamale Cristian-Ioan Vasile Mechanical Engineering and Mechanics Department Lehigh University PA USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper presents a novel framework for inferring timed temporal logic properties from data. The dataset comprises pairs of finite-time system traces and corresponding labels, denoting whether the traces demonstrate specific desired behaviors, e.g. whether the ship follows a safe route or not. Our proposed approach leverages decision-tree-based methods to infer Signal Temporal Logic classifiers using primitive formulae. We formulate the inference process as a mixed integer linear programming optimization problem, recursively generating constraints to determine both data classification, i.e., decision criteria and the tree structure. Applying a max-flow algorithm on the resultant tree transforms the problem into a global optimization challenge, leading to improved classification rates compared to prior methodologies. Moreover, we introduce a technique to reduce the number of constraints by exploiting the symmetry inherent in STL primitives, which enhances the algorithm’s time performance and interpretability. We conduct three case studies involving two-class, multi-class, and complex formula classification scenarios to assess our algorithm’s effectiveness and classification performance.

关键词： Accuracy Transforms Inference algorithms Classification algorithms mixed integer linear programming Complexity theory Logic Decision trees Marine vehicles Optimization

来源：评论

学校读者我要写书评

暂无评论

A two-stage matheuristic for the home healthcare routing and scheduling problem with perishable products

A two-stage matheuristic for the home healthcare routing and...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Aldy Gunawan Nabila Yuraisyah Salsabila Nguyen Pham Kien Minh Vincent F. Yu School of Computing and Information Systems Singapore Management University Singapore Department of Industrial Management National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This study proposes a home healthcare routing and scheduling problem, where perishable products such as medicines, vaccines, or meals must be provided for some patients’ treatments. The problem is formulated as a mixed integer linear programming (MILP). A two-stage matheuristic is then developed as the solution approach. The first stage is a local search to solve the nurse routing problem, and the second stage is run as the relaxed MILP to solve the scheduling problem. The matheuristic is tested on newly generated instances and compared with the results of CPLEX. It is able to obtain CPLEX solutions within shorter computational times for small instances and achieve feasible solutions for larger instances.

关键词： Uncertainty Computer aided software engineering Processor scheduling programming Routing Search problems Robustness Regulation Vaccines mixed integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Inactive Constraint Identification for Unit Commitment by Neural Network

Inactive Constraint Identification for Unit Commitment by Ne...

引用

IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Lishen Wei Liqian Gao Bangxian Zhu Runfeng Zhong Chuanyu Xu Huang Zhou Xiaomeng Ai Jiakun Fang Jinyu Wen State Key Laboratory of Advanced Electromagnetic Technology Huazhong University of Science and Technology Wuhan China Electric Power Research Institute of Guizhou Power Grid Co. Ltd. Guiyang China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

Unit commitment is crucial for optimizing scheduling in power systems and electricity markets. However, because it is typically modeled as a large-scale mixed-integer linear programming problem, its computational efficiency is limited, restricting its further application in the power industry. One significant factor that makes the unit commitment problem challenging is its dense constraints, particularly the numerous power flow constraints due to the transmission limits of the power grid. This paper addresses the challenge by integrating datadriven methods and using neural networks to identify inactive transmission constraints, simplifying the unit commitment model. The proposed method is validated on the RTS-GMLC system, and the results demonstrate that it can effectively identify inactive constraints and improve the computational efficiency of the unit commitment problem.

关键词： Power transmission lines Processor scheduling Computational modeling Neural networks System integration Transmission line measurements Power grids mixed integer linear programming Computational efficiency Bipartite graph

来源：评论

学校读者我要写书评

暂无评论

Energy Coordination Strategy for the Park-Level Integrated Energy System

Energy Coordination Strategy for the Park-Level Integrated E...

引用

Power Science and Technology (ICPST), IEEE International Conference on

作者： Xinyi Li Xiaohua Yang Yongqiang Zhu School of Electrical and Electronic Engineering North China Electric Power University Beijing China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

Integrated energy system (IES) represents a crucial avenue of research in the pursuit of energy conservation and carbon reduction, as it facilitates collaborative management and complementarity among multiple energy sources. This study integrates disparate energy networks within the park into a integrated energy system and formulates coordinated scheduling strategies for multiple energy outputs. Configure rooftop photovoltaic and energy conversion equipment in the system. The operation planning objective of the IES is minimizing annual average cost of the system, while taking into account carbon trading expenses and the advantages of substituting purchased electricity with new energy generation. By considering constraints such as supply-demand balance, energy trading, installation requirements for energy conversion equipment, and energy conversion relationships, a mixed integer linear programming (MILP) algorithm is employed to address the problem. This algorithm enables the determination of installation quantity and configuration capacity of distributed energy, energy trading schemes, and daily operation strategies for the system. The calculation results indicate that the addition of photovoltaic power generation units has a positive effect on reducing system carbon emissions and lowering carbon trading costs. Furthermore, energy conversion devices enhance system resilience by efficiently absorbing new energy generation during winter and summer, selling excess electricity to the grid during spring and autumn, and ensuring a stable supply of thermal energy and natural gas.

关键词： Photovoltaic systems Costs Electricity Energy conversion Emissions trading Planning mixed integer linear programming

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：