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检索条件"主题词=Mixed integer linear programming"

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A Solution Based on Hub Selection and Robot Routing Optimization for Last-mile Delivery

A Solution Based on Hub Selection and Robot Routing Optimiza...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Maria A. del Cacho Estil-les Wasim A. Ali Maria Pia Fanti Mario Binetti Agostino M. Mangini Department of Electrical and Information Engineering Polytechnic of Bari Italy DICATECh Polytechnic of Bari Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This paper addresses the challenges in last-mile delivery by proposing an innovative solution employing Hub-and-Robots routing, strategically utilizing park-and-ride facilities as central hubs to optimize urban delivery operations. The increasing demand for rapid and efficient deliveries has necessitated a reevaluation of traditional delivery methodologies. The study focuses on optimizing last-mile delivery operations, minimizing the total distance of the routes traveled by robots, while satisfying customer requirements. Hub selection, leveraging existing infrastructure, and the potential use of park-and-ride facilities emerge as key considerations. The optimization model is applied to a case study involving two districts of the center of Bari (a city of Southern Italy) and a simulation validates the obtained results.

关键词： Systematics Computer aided software engineering Optimization models Scalability Heuristic algorithms Urban areas Routing mixed integer linear programming Resource management Optimization

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Research of Greenhouse Heating Based on Photovoltaic, Heat Pump and Thermal Storage System: A Case Study in Beijing

Research of Greenhouse Heating Based on Photovoltaic, Heat P...

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Energy Engineering and Power Systems (EEPS), International Conference on

作者： Zhehan Zhong Jixue Wang Guodong Chen Bing Liu Xiaolei Li Shuo Yang Zheng Li Electric Power Planning & Engineering Institute Beijing China Department of Energy and Power Engineering Tsinghua University Beijing China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

This study focuses on the global demand for renewable energy heating, and proposes a scheme that combines photovoltaic panels, heat pumps, and thermal storage to offer heat to agricultural greenhouses. Initially, a computational model of the system is developed, with the economic aspect as the objective function, energy and power balances as constraints, actual meteorological conditions of Beijing as boundary conditions. Subsequently, the model is optimized through the MILP (mixed integer linear programming) in Gurobi to ascertain the minimal annual cost of the system and the scales of its components. Finally, a comparative analysis with the prevailing heating price of Beijing reveals the proposed scheme's technological and financial viability.

关键词： Photovoltaic systems Renewable energy sources Costs Heat pumps Cogeneration Computational modeling Greenhouses linear programming mixed integer linear programming Resistance heating

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Reliability Assessment of Distribution Systems Considering the Effects of Cyber Failures

Reliability Assessment of Distribution Systems Considering t...

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Intelligent Power and Systems (ICIPS), International Conference on

作者： Xuan Fang Wenrui Zhou Jiahao Liang Juntao Li Siguang Zheng Bohuai Yan Guangzhou Bureau of China Southern Power Grid EHV Transmission Company Guangzhou China College of Electrical Engineering & New Energy China Three Gorges University Yichang China The School of Electrical and Information Engineering Tianjin University China College of Science Hongkong Baptist University Hongkong China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

The traditional reliability assessment methods for cyber-physical distribution systems suffer from low computational efficiency and accuracy, as well as insufficient consideration of cyber systems. This article deeply analyzes the impact of cyber systems failures on the reliability of distribution networks, and uses optimization methods to solve the reliability of distribution systems. The reliability assessment method proposed in this article has the advantage of precise evaluation.

关键词： Accuracy Optimization models Distribution networks Planning mixed integer linear programming Computational efficiency Reliability Information systems

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The Vehicle Routing Problem with Drones and Flexibility Demands

The Vehicle Routing Problem with Drones and Flexibility Dema...

引用

Congress on Evolutionary Computation

作者： Tran Thi Hue Bao Nguyen Quoc Nguyen Pham Phu Manh Nguyen Khanh Phuong Huynh Thi Thanh Binh Dang Quang Thang Hanoi University of Science and Technology Hanoi Vietnam Banking Academy of Vietnam

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

In recent years, the Vehicle Routing Problem, with its variants handling complex realistic constraints, continues to be a key area of research, reflecting its enduring importance in modernized societies. Nevertheless, less attention has been paid to the variant with the flexibility of customer demands. This paper introduces the problem of addressing the integration of drones into the existing transportation system to maximize the profit of distributing freight during a limited working time by allowing flexibility in the delivered quantity. We propose a mixed integer linear programming (MILP) formulation and a genetic algorithm (GA) to solve the problem. To assess the proposed algorithm, we create the benchmark instances of the problem from published data sources. Experimental results on the instances show a significantly better performance of our proposal than MILP. Moreover, we evaluate our approach by comparing its performance with existing solutions in published closely related works.

关键词： Power demand Soft sensors Vehicle routing Transportation Benchmark testing mixed integer linear programming Proposals

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ST-MAC: Spatial-Temporal MAC Scheduling for Underwater Sensor Networks

ST-MAC: Spatial-Temporal MAC Scheduling for Underwater Senso...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： C.-C. Hsu K.-F. Lai C.-F. Chou K. C.-J. Lin Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)9781424435128

Underwater sensor networks (UWSNs) have attracted a lot of attention recently. Since data in UWSNs are transmitted by acoustic signals, the characteristics of a UWSN are different from those of a terrestrial sensor network. In other words, the high propagation delay of acoustic signals in UWSNs causes spatial-temporal uncertainty, and makes transmission scheduling in UWSNs a challenging problem. Hence, in this paper, we propose a spatial-temporal MAC scheduling protocol, called ST-MAC, which is designed to overcome spatial-temporal uncertainty based on TDMA-based MAC scheduling for energy saving and throughput improvement. We construct the spatial-temporal conflict graph (ST-CG) to describe the conflict delays among transmission links explicitly, and model ST-MAC as a new vertex coloring problem of ST-CG. We then propose a novel heuristic, called the traffic-based one-step trial approach (TOTA), to solve the coloring problem. In order to obtain the optimal solution of the scheduling problem, we also derive a mixed integer linear programming (MILP) model. Finally, we present a comprehensive performance study via simulations. The results show that ST-MAC can perform better than existing MAC schemes (such as S-MAC, ECDiG, and T-Lohi) in terms of the network throughput and energy cost.

关键词： Sensor phenomena and characterization Acoustic sensors Underwater acoustics Uncertainty Media Access Protocol Throughput Propagation delay Traffic control mixed integer linear programming Costs

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Advancing Multi-Energy Hub Design: an Integrated Approach for Optimizing Residential Clusters in High RES Penetration Scenarios

Advancing Multi-Energy Hub Design: an Integrated Approach fo...

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International Conference on Smart Energy Systems and Technologies (SEST)

作者： Marialaura Di Somma Lingkang Jin Nicola Bianco Christina Papadimitriou Department of Industrial Engineering University of Naples Federico II Naples Italy Electrical Engineering Department Eindhoven University of Technology Eindhoven Netherlands

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

With the energy transition underway, the wider penetration of multi-energy hubs (MEHs) is inevitable as they allow for the integration of multiple energy carriers at the local level and especially at the users' side by enhancing flexibility of energy supply and renewabIes penetration. Thus, addressing their design properly is imperative. While numerous energy modeling software and tools are extensively discussed in the literature, they primarily focus on a single energy carrier, mainly dedicated to the electrical network. In this study, an optimization planning tool capable of analyzing the synergies of various energy carriers is presented. The tool aims to determine the optimal configuration of MEHs with sizes of the chosen technologies based on the modeler's preferences. The tool offers flexibility in modelling a wide range of technologies as potential options for the optimal configuration, and in considering different types of objectives as economic and environmental ones that can be assessed through a multi-objective approach. It is formulated through mixed-integer linear programming in a modular manner, facilitating the easy implementation of new emerging technologies, by enhancing scalability and applicability in real context. To prove the effectiveness of the optimization tool, it is applied for the design of a MEH for a residential building cluster located in Torino (Italy). Different scenarios are analyzed to determine the impact of high levels of renewabIes penetration on the design of the MEH while guaranteeing the economic sustainability of the solution.

关键词： Economics Scalability Biological system modeling Buildings linear programming Software Planning mixed integer linear programming Sustainable development Optimization

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A Multi-Objective Train Timetable Rescheduling Model During the Transitional Period

A Multi-Objective Train Timetable Rescheduling Model During ...

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International Conference on Intelligent Transportation

作者： Hao Peng Shiqi Zhang Shuai Su Du Shang Zhikai Wang State Key Laboratory of Advanced Rail Autonomous Operation Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing P. R. China Beijing Mass Transit Railway Operation Co. Ltd.

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In a metro system, train delays cause inconvenience to passengers and render the scheduled timetable infeasible. This paper addresses the problem of train timetable rescheduling and rolling stock circulation planning, with a particular focus on train delays occurring during the transitional period from peak to off-peak hours. Considering both operating costs and passenger service quality, this paper proposes a multi-objective optimization model to minimize the number of stranded passengers at platforms, train delays, and train service cancellations. Additionally, a strategy of adding temporary train services is considered to accommodate the change in passenger flow. Further, some linearization methods are used to transform this model into a mixed integer linear programming (MILP) problem, which can be effectively solved using the CPLEX optimizer. Finally, computational experiments are conducted using realistic case studies based on the Beijing Yizhuang line, incorporating scenarios with randomly induced delays. The experimental results show that the proposed rescheduling method in this study can reduce the number of stranded passengers due to train delays during the transitional period, and a feasible solution can be found in a short time.

关键词： Costs Computational modeling Optimization models Transforms Delays Planning mixed integer linear programming Computational efficiency Artificial intelligence Intelligent transportation systems

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Practical Approach to Identifying Additive Link Metrics with Shortest Path Routing

Practical Approach to Identifying Additive Link Metrics with...

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IEEE Global Communications Conference

作者： Xiong Wang Mehdi Malboubi Sheng Wang Shizhong Xu Chen-Nee Chuah Key Lab of Optical Fiber Sensing & Communications School of Communication & Information Engineering University of Electronic Science & Technology of China Department of Electrical & Computer Engineering University of California

ISBN: (纸本)9781479959532

We revisit the problem of identifying link metrics from end-to-end path measurements in practical IP networks where shortest path routing is the norm. Previous solutions rely on explicit routing techniques (e.g., source routing or MPLS) to construct independent measurement paths for efficient link metric identification. However, most IP networks still adopt shortest path routing paradigm, while the explicit routing is not supported by most of the routers. Thus, this paper studies the link metric identification problem under shortest path routing constraints. To uniquely identify the link metrics, we need to place sufficient number of monitors into the network such that there exist m (the number of links) linear independent shortest paths between the monitors. In this paper, we first formulate the problem as a mixed integer linear programming problem, and then to make the problem tractable in large networks, we propose a Monitor Placement and Measurement Path Selection (MP-MPS) algorithm that adheres to shortest path routing constraints. Extensive simulations on random and real networks show that the MP-MPS gets near-optimal solutions in small networks, and MP-MPS significantly outperforms a baseline solution in large networks.

关键词： shortest-path routing explicit route practical methods mixed integer linear programming Internet Protocol networks MONITOR Metronidazole source routing shortest path multiprotocol label switching

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Logical analysis of multi-class data

Logical analysis of multi-class data

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Conferencia Latinoamericana En Informatica (CLEI)

作者： Juan Félix Avila-Herrera Munevver Mine Subasi Escuela de Informática Universidad de Costa Rica Department of Mathematical Sciences Florida Institute of Technology Florida USA

Logical Analysis of Data (LAD) is a two-class learning algorithm which integrates principles of combinatorics, optimization, and the theory of Boolean functions. This paper proposes an algorithm based on mixed integer linear programming to extend the LAD methodology to solve multi-class classification problems, where One-vs-All (OvA) learning models are efficiently constructed to classify observations in predefined classes. The utility of the proposed approach is demonstrated through experiments on multi-class benchmark datasets.

关键词： Algorithm design and analysis Data mining Standards Optimization Boolean functions Benchmark testing mixed integer linear programming

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Increasing waiting time satisfaction in parallel job scheduling via a flexible MILP approach

Increasing waiting time satisfaction in parallel job schedul...

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Stephan Schlagkamp Matthias Hofmann Lars Eufinger Rafael Ferreira da Silva Robotics Research Institute TU Dortmund University Institute of Transport Logistics TU Dortmund University Information Science Institute University of Southern California

Scheduling of jobs in parallel computing is crucial to efficiently use shared resources, while attaining user satisfaction. In this paper, we evaluate how mixed-integer linear programming (MILP) can be applied for the online parallel job scheduling problem (which is well-known to be an NP-complete problem). Therefore, we introduce the idea of planning horizons for parallel job scheduling, and provide a MILP formulation of the targeted scheduling problem. Due to the linear fashion of possible MILP objective functions, the proposed scheduling algorithm is flexible towards different optimization goals. We make use of data collected in a user-based study and workload traces from two real production systems, and demonstrate that our approach suffices to increase users' waiting time satisfaction. Additionally, we show that our MILP formulation outperforms the EASY scheduling technique with conservative backfilling, when neglecting the online character of job submissions.

关键词： Processor scheduling Optimization Schedules Complexity theory mixed integer linear programming

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