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

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An Optimization Design for a Half-Closed-Loop Logistics Network with Uncertainty

An Optimization Design for a Half-Closed-Loop Logistics Netw...

引用

International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Xiao-Hui Qin Huai-Zhen Ye Cheng-Hu Yang College of Logistics Southwest Jiaotong University Chengdu Sichuan China

A two-echelon half-closed-loop logistics network system is founded for the issue of manufacturing logistics network design, including supply and return channels. Considering the integration of the uncertainty and cycle time of the demand quantities of products and the return rates of used products, sites selection of potential logistics centers, plants and recycling plants, and transshipment problem, a stochastic, multi-time-step, capacitated mixed integer linear programming model is presented, the objective function makes total costs including fixed costs, transportation costs and storage costs in logistics centers minimize. Since such network design problems belong to a class of NP hard problems, a genetic algorithm approach-based heuristic to this model is presented. Finally a numerical example is used to prove the model and genetic algorithm validity.

关键词： Design optimization Logistics Uncertainty Cost function Genetic algorithms Manufacturing Recycling Stochastic processes mixed integer linear programming Road transportation

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Decision Making among Alternative Routes for UAVs in Dynamic Environments

Decision Making among Alternative Routes for UAVs in Dynamic...

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12th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA 2007), vol.2

作者： Jose J. Ruz Orlando Arevalo Gonzalo Pajares Jesus M. de la Cruz Department of Computer Architecture and Automatic Control Universidad Complutense de Madrid Spain Department of Software Engineering and Artificial Intelligence Universidad Complutense de Madrid Spain

This paper presents an approach to trajectory generation for Unmanned Aerial Vehicles (UAV) by using mixed integer linear programming (MILP) and a modification of the A{sup}* algorithm to optimize paths in dynamic environments, particularly having pop-ups with a known future probability of appearance. Each pop-up leads to one or several possible evasion maneuvers, characterized with a set of values used as decision making parameters in an integer linear programming (ILP) model that optimizes the final route by choosing the most suitable alternative trajectories, according to the imposed constrains such as maximum fuel consumption and spent time. The model of the system in MILP and A{sup}* algorithms is presented, as well as the ILP formulation for decision making. Results and discussions are given to promote future real time implementations.

关键词： Decision making Unmanned aerial vehicles Vehicle dynamics Path planning Dynamic programming mixed integer linear programming integer linear programming Radar tracking Military aircraft Computer architecture

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Faulty model identification in deterministic labeled Time Petri nets

Faulty model identification in deterministic labeled Time Pe...

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International Workshop on Discrete Event Systems, WODES

作者： Francesco Basile Pasquale Chiacchio Jolanda Coppola Ingegneria dell'Informazione Univ. di Salerno Italy

In a previous paper we presented an approach to identify a faulty model for timed discrete event systems when the nominal model is known, given a set of observed timed sequences. The approach works with Time Petri net models and is based on the formulation of a mixed-integer linear programming Problem derived from a set of logical predicates. The faulty behavior is modeled by adding fault transitions. In this paper we extend this approach by allowing that two transitions may share the same event label. The nominal model is a deterministic labeled Time Petri net system. The identification problem can still be solved via a mixed-integer linear programming Problem but the constraint set previously determined is modified.

关键词： Petri nets Labeling Fault diagnosis mixed integer linear programming Circuit faults Upper bound Conferences

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Integrated Optimization on Tugboat Scheduling and Berth Allocation of Seaside Port Operations

Integrated Optimization on Tugboat Scheduling and Berth Allo...

引用

Automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Mingkai Zou Yaqiong Lv School of Transportation and Logistics Engineering Wuhan University of Technoloty Wuhan China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

The current inefficiency in seaside operations at the port terminal has led to excessive waiting times for ships and environmental pollution. Traditional decision-making methods for berth allocation and tug scheduling plans have resulted in inefficiencies in the overall integrated process. In this study, a new mixed-integer linear programming model for optimizing tugboat scheduling and berth allocation at seaside port terminals is presented, aiming to minimize the weighted total stay time of ships while addressing the complexities of tugboat matching constraints, ship shift movements, and the heterogeneity of berths. Through computational experiments utilizing both practical port data and randomly generated instances, the model demonstrates significant improvements in operational efficiency and environmental impact reduction compared to traditional port scheduling methods. By focusing on the optimization of resource allocation and scheduling, the proposed model offers a comprehensive solution to the current inefficiencies faced by port terminals, highlighting its potential for practical implementation and its contribution towards more sustainable and effective port operations.

关键词： Job shop scheduling Pollution Processor scheduling Computational modeling Seaports mixed integer linear programming Manufacturing Resource management Marine vehicles Optimization

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A heuristic approach to optimize radial inter-array cabling topologies in large wind power plants

A heuristic approach to optimize radial inter-array cabling ...

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IEEE General Meeting Power& Energy Society

作者： Ramon Abritta Alexey Pavlov Damiano Varagnolo Børre Tore Børresen Dept. of Geoscience and Petroleum Norwegian University of Science and Technology Trondheim Norway Dept. of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway Research Center Equinor ASA Trondheim Norway

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

We propose and analyze an algorithm for planning the topology of the inter-array cables that, in a wind power plant (WPP), link the wind turbine generators (WTGs) to the substation. The approach embeds a heuristic step that significantly reduces the complexity of planning the radial inter-array cable topology for large WPPs, which is generally an NP-hard mixed-integer linear programming problem. The heuristic seeks to reduce the number of decision variables by utilizing user-defined parameters to exploit characteristics of the WPPs layouts. We demonstrate the effectiveness of the heuristic by comparing its cost-saving potentials against another state-of-the-art method on three use-cases regarding real WPPs. In terms of solution quality, the results indicate that, among all study cases, the proposed strategy either compares favorably or has a similar performance to the method from the literature.

关键词： Substations Layout Voltage Wind power generation Generators Topology Planning Wind turbines mixed integer linear programming Cables

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Coordination Framework for Integrated Operation of Water-Power Systems under Contingencies

Coordination Framework for Integrated Operation of Water-Pow...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Mohannad Alhazmi Payman Dehghanian Mostafa Nazemi Fei Wang Abdullah Alfadda George Washington University Washington DC USA

ISBN: (纸本)9781728164021

With the sharply-growing complexity and rapid deployment of smart technologies in our modern society, there is an urgent call for risk-aware management and coordination in day-to-day operation of the interlinked critical infrastructures. In particular, the interconnected Water and Power Systems (WaPS) stands out, urgently in need of joint and cooperative operation to maximize the economic benefits during normal operating conditions and resilience services during emergencies. The inter-dependency of WaPS is crucial for emergency response to High Impact Low Probability (HILP) incidents, the frequency and intensity of which have been recently on the rise. While contingency analysis is used to assist the system operators in gaining knowledge of the system's static security, such understanding is more challenging to achieve in the case of integrated WaPS. This paper proposes a novel optimization model for under-emergency operation of the integrated WaPS, considering contingencies in both networks. In order to ensure the delivery of water demand, the proposed formulation considers the hydraulic constraints of the water networks, which is naturally a nonlinear model. The proposed nonlinear model is approximated using a piece-wise linearization approach to convert the optimization model into a mixed-integer linear programming (MILP) formulation. The proposed analysis is applied to a modified IEEE 24-bus reliability test system that is jointly operated with two commercial-scale water networks. The proposed model is evaluated using various disaster severity levels, revealing significant resilience benefits.

关键词： Systems operation Simulation Hydraulic systems Power system reliability mixed integer linear programming Reliability Security

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Energy Management System for the CN MOST Laboratory at the Savona University Campus

Energy Management System for the CN MOST Laboratory at the S...

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IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI)

作者： Matteo Fresia Tommaso Robbiano Silvia Siri Stefano Bracco DITEN department University of Genoa Genova Italy DIBRIS department University of Genoa Genova Italy

ISBN: (数字)9798350362138

ISBN: (纸本)9798350362145

This paper proposes a mixed-integer linear programming model for the energy management system of the new research laboratory that will be installed in the Savona Campus of the University of Genova, benefitting from the fundings of the Italian National Center for Sustainable Mobility. This energy management system is able to daily manage the nanogrid feeding the laboratory which will be equipped with a photovoltaic plant and a battery energy storage system, and will have to feed electric loads of the laboratory and a set of autonomous mobile robots used to execute different delivery tasks within the campus. The proposed energy management system optimizes power flows and robot task scheduling in order to minimize the operating costs, the curtailment of the photovoltaic source and the number of unperformed tasks. The application of the proposed mathematical formulation to the real case of the Savona Campus is presented and discussed in the paper.

关键词： Photovoltaic systems Technological innovation Uncertainty Service robots Real-time systems Mathematical models mixed integer linear programming Mobile robots Energy management systems Optimization

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Fuzzy milp unit commitment incorporating wind generators

Fuzzy milp unit commitment incorporating wind generators

引用

IEEE General Meeting Power& Energy Society

作者： Bala Venkatesh Peng Yu Dechen Choling H. B. Gooi Ryerson University Canada Nanyang Technological University Singapore

Summary form only given. Day-ahead unit commitment (UC) solution methods seek to determine the status and output of all available generators. In a world with an increasing integration of renewable energy sources such as wind electric generators (WEG), the UC solution process must model and include WEGs too in the decision making process. Power output of WEGs in a day-ahead decision making process are usually modeled using a short term probabilistic forecast. Inclusion of WEGs introduces uncertainty in the solution that may be quantified through an imbalance risk function. Thus a UC solution method should seek a solution to minimize cost and risk in schedule. Two strategies are proposed in this paper to minimize costs and handle risks introduced due to WEGs. These formulations are posed as fuzzy optimization models and are solved using the MILP (mixed integer linear programming) technique. The proposed strategies are tested on a 26 and a 100-generator systems with associated transmission networks that have 3 and 6 wind generators each. The results with two strategies of handling WEGs are discussed.

关键词： Wind energy generation Decision making Costs Renewable energy resources Generators Predictive models Wind forecasting Uncertainty mixed integer linear programming System testing

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Reconfiguration-Aware Task Graph Scheduling

Reconfiguration-Aware Task Graph Scheduling

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IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC

作者： Hessam Kooti Eli Bozorgzadeh Google Inc. Mountain View CA USA Computer Science Department University of California Irvine CA USA

Due to increasing demand for reconfigurability in embedded systems, real-time task scheduling is challenged by non-negligible reconfiguration overheads. We introduce the problem of real-time task scheduling under reconfiguration overhead on heterogeneous reconfigurable systems while considering the data dependencies and data communication overhead. We introduce a novel graph representation which captures the delay overhead due to data dependencies and reconfiguration. We formulate the problem as a network flow problem and provide a mixed integer linear programming solution to minimize the completion time so called makespan. Results show that our proposed scheduling improves the makespan by 24.20% (on average) in comparison with maximum-transition-overhead scheduling.

关键词： Processor scheduling Real-time systems Program processors Bandwidth Hardware mixed integer linear programming Embedded systems

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Energy Management Strategy based on Hybrid-Systems Algorithm and Radial Basis Function Neural Network for HEV

Energy Management Strategy based on Hybrid-Systems Algorithm...

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Chinese Automation Congress (CAC)

作者： Baoshuai Liu Hui Liu Lijin Han Xiaolei Ren School of Mechanical Engineering Beijing Institute of Technology Beijing China Beijing Institute of Technology Institute of Advanced Technology Jinan China

ISBN: (纸本)9781665426480

In the paper, an energy management strategy (EMS) based on the hybrid system predictive control algorithm and radial basis function neural network algorithm (RBFNN) is constructed for hybrid electric vehicle(HEV). First, an velocity predictor is proposed based on the RBF-NN and the Chebyshev filter, which aim to improve the calculated accuracy. Based on the detailed analysis, the driveline system is simplified into an hybrid dynamic system and optimized by mixed integer linear programming algorithm. Through the simulation, the effectiveness of the proposed method is validated in two driving cycles. Results show that the proposed approach improve the internal combustion engine (ICE) fuel economy.

关键词： Heuristic algorithms Radial basis function networks Fuel economy Filtering algorithms Chebyshev approximation Prediction algorithms mixed integer linear programming

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