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检索条件"主题词=mixed-integer linear programming"

共 2269 条记录，以下是631-640 订阅

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Optimization of the design and operation of low-carbon aggregated energy systems 4

Optimization of the design and operation of low-carbon aggre...

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4th EAGE Digitalization Conference and Exhibition

作者： Sala, S. Amendola, A. Gioco, G. Primato, M. Aceto, C. Belverato, D. Martelli, E. Dipierro, V. Alpegiani, F. Eni Spa Italy Politecnico di Milano Italy

ISBN: (纸本)9789462824850

The so-called Aggregated Energy Systems (AES) represent an opportunity to satisfy the energy demand more efficiently, and economically with respect to traditional energy systems. For instance, this may be achieved by the integration of variable (renewable) and dispatchable energy sources (e.g. gas turbines), possibly integrated with both seasonal and short-duration storage systems. To support optimal design and operation of AES, optimization tools based on a linear programming (LP) or mixed-integer linear programming (MILP) formulation are commonly employed. In this work, we have developed a MILP optimization model tailored to the design of utilities systems for heat and power generation in upstream facilities. The tool is suitable for particularly challenging scenarios (e.g. FPSOs) where traditional generation is integrated with variable renewables. © 4th EAGE Digitalization Conference and Exhibition 2024.

关键词： mixed-integer linear programming

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Probabilistic Safety Verification of Stochastic Hybrid Systems Using Probably Approximately Correct Barrier Certificates

Probabilistic Safety Verification of Stochastic Hybrid Syste...

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2024 International Conference on Intelligent Computing and Data Mining, ICDM 2024

作者： Yang, Zixuan East China Normal University Software Engineering Institute Shanghai China

ISBN: (纸本)9798331506261

The probabilistic safety verification problem of stochastic hybrid systems is very important. In this paper, for a given stochastic hybrid system, an algorithm for generating probabilistic barrier certificates is proposed to verify the safety of the system. By solving the mixed integer programming model, the solution of probabilistic barrier certificate is transformed into an optimization problem. This paper implements the probabilistic barrier certificate generation tool PBC and evaluates its performance on three benchmark systems. Experimental results show that compared with the existing methods PBCG, PBC can verify the safety of the system with a higher success probability. © 2024 IEEE.

关键词： mixed-integer linear programming

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Deployment of Dynamic Defense Strategies for Multiple Devices in the Industrial Internet Based on Zero Trust

Deployment of Dynamic Defense Strategies for Multiple Device...

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2024 China Automation Congress, CAC 2024

作者： Wang, Mo Gao, Jianlei Li, Yun Wang, Zhe Gong, Tianyu China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798350368604

This paper proposes an algorithm for deploying dynamic defense strategies on multiple devices in the industrial Internet based on zero trust, aiming at coping with complex and ever-changing security challenges. Malicious devices are identified through a submodular optimization algorithm, and defense strategies are dynamically allocated using mixed integer programming to ensure efficient protection of the system. This paper describes in detail the malicious devices feature analysis, the reverse strategy deviation algorithm, and the defense strategy allocation model, and verifies the effectiveness of the proposed algorithm through simulation experiments. The results show that the algorithm can maximize the security of the system under limited resources, respond to changes in device priorities and task requirements in real-time, and provide a new solution for security protection in the industrial Internet environment. © 2024 IEEE.

关键词： mixed-integer linear programming

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A HEURISTIC ALGORITHM FOR SOLVING LOAD-DEPENDENT VEHICLE ROUTING PROBLEM 51

A HEURISTIC ALGORITHM FOR SOLVING LOAD-DEPENDENT VEHICLE ROU...

引用

51st International Conference on Computers and Industrial Engineering, CIE 2024

作者： Trang, N.T. Tai, P.D. Buddhakulsomsiri, J. Parthanadee, P. School of Manufacturing Systems and Mechanical Engineering Sirindhorn International Institute of Technology Thammasat University Pathum Thani12000 Thailand Department of Agro-Industrial Technology Faculty of Agro-Industry Kasetsart University Bangkok Thailand

This paper explores a class of vehicle routing problems that considers the load-dependent distance objective function instead of the total distance. The problem, originating from Thailand's e-commerce delivery business, is formulated as a mixed-integer linear programming model. Since only problem instances of small scale can be solved using the mathematical model, a heuristic algorithm is developed to handle large-scale instances. The algorithm features a load-dependent distance savings algorithm for clustering, and the mathematical model is used for the re-optimization of each cluster. The effectiveness of both the exact method and heuristic is evaluated on several problem instances modified from a standard library. The results indicate that the heuristic can reach near-optimal solutions for instances with known optimal solutions. For those with only lower bounds, solutions from the heuristic show relatively small gaps compared to that of the MILP. In terms of computational time, it is observed that the heuristic algorithm takes a significantly shorter time, especially for larger problem instances, to find a solution than does the mathematical model. © 2024 Computers and Industrial Engineering. All rights reserved.

关键词： mixed-integer linear programming

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Research on the Optimization of Reverse Logistics Networks for End-of-Life Vehicles 12

Research on the Optimization of Reverse Logistics Networks f...

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12th International Symposium on Project Management, ISPM 2024

作者： Cao, Junya School of Management ZhengZhou University Henan Zhengzhou450000 China

ISBN: (纸本)9798331302344

In recent years, with the vigorous development of China's economy, various industries have made significant progress, and the automotive industry is no exception. China's automobile production and sales are now leading the world by a significant margin. However, the importance of the end-of-life vehicle recycling industry cannot be overlooked. end-of-life vehicle recycling offers substantial economic and environmental benefits and can become a new growth point, alleviating burdens on the automotive industry. This paper constructs a mixed-integer programming model to minimize the total cost within the entire reverse logistics network, incorporating necessary constraints to calculate the optimal node selection and flow distribution in the network. An empirical study is conducted on Henan Province. Using Lingo software, the optimal locations for the candidate nodes and the flow distribution between nodes are determined, effectively improving the efficiency of the reverse logistics network and reducing transportation costs. This achieves the goal of optimizing the reverse logistics network for end-of-life vehicles in Henan Province. © 2024 ISPM. All Rights Reserved.

关键词： mixed-integer linear programming

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A REINFORCEMENT LEARNING APPROACH FOR PRODUCTION SCHEDULING IN INDUSTRY 4.0 CONSIDERING LIMITED DATA

A REINFORCEMENT LEARNING APPROACH FOR PRODUCTION SCHEDULING ...

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ASME 2024 International Mechanical Engineering Congress and Exposition, IMECE 2024

作者： Lopez-Salazar, Camilo Ekwaro-Osire, Stephen Ekwaro-Osire, Henry Hopfmüller, Stephan Dept. of Mechanical Engineering Texas Tech University United States BIBA - Bremer Institut für Produktion und Logistik Bremen Germany Bremen Germany

ISBN: (纸本)9780791888698

As the global pursuit of net-zero emissions by 2050 intensifies, the role of renewable energy sources such as solar photovoltaics becomes increasingly relevant. However, their intermittent nature and energy price volatility present challenges for energy-intensive sectors like manufacturing. Integrating renewables into production schedules emerges as a strategy to mitigate costs and environmental impact. Industry 4.0 technologies, particularly machine learning, offer opportunities for optimizing energy consumption. This paper introduces a NeuroEvolution of Augmented Topologies (NEAT) algorithm for energy management operations tailored for industrial prosumers. Inspired by the evolution of biological nervous systems, NEAT evolves a neural network's topology and parameters to make optimal decisions for a given environment. The study's objective is to generate a day-ahead energy schedule that considers renewable energy and primary grid utilization using limited information on the system's current state. A comparative analysis between the NEAT scheduler, a traditional supervised learning-based scheduler, and a deterministic mixedinteger linear programming (MILP) solver as a baseline demonstrates the effectiveness and robustness of the proposed method, which reduced the electricity bill by 18.69% over one week of real data simulation, using just six hours of previous measurements. Copyright © 2024 by ASME.

关键词： mixed-integer linear programming

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M5Use: An Optimization Framework for the Multi-Use Operation Scheduling of Large-Scale Battery Storage Systems

M5Use: An Optimization Framework for the Multi-Use Operation...

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2024 IEEE PES Innovative Smart Grid Technologies Europe

作者： Cortes, Mauricio Celi Nsir, Najet Koltermann, Lucas Zurmuehlen, Sebastian van Ouwerkerk, Jonas Sauer, Dirk Uwe Rhein Westfal TH Aachen Inst Power Elect & Elect Drives ISEA D-52074 Aachen Germany

ISBN: (纸本)9798350390438;9798350390421

Large-scale battery storage systems (BESS) have found widespread application in frequency regulation and spot markets across Europe. However, combined multi-use approaches are necessary to achieve an economically robust operation of BESS. In this context, we present a flexible modeling and optimization framework to find the optimal utilization strategy for BESS in multi-use and single application. Using this framework, we evaluate applications such as energy arbitrage, frequency containment reserve (FCR), and automatic frequency restoration reserve (aFRR) in single and combined operation for the the 5 MW/7.5 MWh BESS M5BAT located in Aachen, Germany. We found that combined FCR, aFRR, and arbitrage operation results in 196% higher revenues than single FCR operation, which is the current application of M5BAT. Furthermore, we observed synergies between applications that result in revenue without physical delivery. Our results indicate the advantages of multi-use operation of BESS while our framework represents a tool for its realization.

关键词： large-scale battery storage systems life cycle costs mixed-integer linear programming multi-use operation value-stacking

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A mixed integer linear Program for Post-translational Modification Characterization

A Mixed Integer Linear Program for Post-translational Modifi...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Lai, Shengzhi Zhao, Peize Li, Ning Yu, Weichuan The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong The Hong Kong University of Science and Technology Interdisciplinary Programs Office Hong Kong Hkust Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China The Hong Kong University of Science and Technology Division of Life Science Hong Kong

ISBN: (纸本)9798350386226

Characterizing post-translational modifications (PTMs) is crucial due to their vital role in regulating cellular activities. Current database search methods for peptide identification and PTM characterization face the challenge of exponentially increasing number of PTM combinations. Consequently, these methods resort to enumerating a small fraction of the PTM combinations. However, based on our analysis, more than 99% of the PTM combinations (up to three PTMs) are infeasible as their total mass does not match the mass shift between the precursor mass and theoretical mass. Enumerating those infeasible combinations is unnecessary and would lead to unsatisfactory performance. To address this issue, we propose a two-step method for characterizing multiple PTMs with a reduced search space of feasible PTM combinations only. The method first uses a mixed integer linear program (MILP) to collect feasible peptide sequences and PTM mass combinations. Then, these feasible peptides are exhaustively examined to find the optimal one. We conducted comprehensive experiments to evaluate the method's performance. When applied to a soybean data set, our method has better performance than a representative tag-based search engine. The effectiveness of search space reduction and the sensitivity and precision of our method are demonstrated. © 2024 IEEE.

关键词： mixed-integer linear programming

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Optimal MBU Positioning under Fault Scenario for Distribution Networks with high PV Penetration 14

Optimal MBU Positioning under Fault Scenario for Distributio...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Caruana, Cedric Bhattacharya, Somesh Raute, Reiko Micallef, Alexander Scerri, Kenneth Department of Electrical Engineering Faculty of Engineering University of Malta Msida Malta Department of Systems and Control Faculty of Engineering University of Malta Malta

ISBN: (纸本)9781837242689

Faults on distribution networks due to abnormal weather events can lead to disruption and can cause high socio-economic losses. In line with the rising frequency of such events, the paper proposes an algorithm for the optimal deployment of mobile battery units to restore sections of the network. The considered battery units are rated at 1MVA to keep them realistic for the mobile application. The placement algorithm is formulated as a mixed integer mathematical optimisation problem. Sectionalising/tie switches are assumed on each branch of the network in order to increase the restoration configuration flexibility. Photovoltaic systems, distributed along the network, are allowed to contribute to the restored network sections. A number of critical loads are defined and these are prioritised in the restoration process. The objective function also considers the reduction of the overall renewable energy curtailment. The performance of the algorithm is tested on the IEEE 33 bus network with four tie lines. Scenarios with increasing levels of PV power are considered and the effect of incorporating the PV power is studied. © The Institution of Engineering & Technology 2024.

关键词： mixed-integer linear programming

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A Bi-Level Optimization Model for Citizen Energy Communities Towards Sustainable Development: A Stackelberg Game Theory Approach 9

A Bi-Level Optimization Model for Citizen Energy Communities...

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9th International Conference on Technology and Energy Management, ICTEM 2024

作者： Mobahseri, Sahar Rashidinejad, Masoud Abdollahi, Amir Mollahassanipour, Mojgan Dorahaki, Sobhan Shahid Bahonar University of Kerman Department of Electrical Engineering Kerman Iran University of Sistan and Baluchestan Faculty of Electrical and Computer Engineering Zahedan Iran

ISBN: (纸本)9798350329797

This paper presents a Stackelberg game bi-level decision-making framework for optimizing the operation of multi-Citizen Energy Communities (CECs) in an energy market. The framework considers the interaction between the distribution grid and downstream CECs, with the objective of maximizing the profit of the distribution company (DISCO) and reducing pollution at the upper level, and minimizing the cost of CECs and reducing carbon emissions at the lower level. The proposed nonlinear bi-level model is transformed into a mixed-integer linear programming (MILP) model using Karush-Kuhn-Tucker (KKT) conditions and duality theory. The effectiveness of the model is evaluated using a distribution test system. This paper highlights the importance of CECs in achieving a green and sustainable society, and provides a practical and efficient solution for optimizing their operation in an energy market. © 2024 IEEE.

关键词： mixed-integer linear programming

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