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

共 2269 条记录，以下是551-560 订阅

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linear programming Method for Distribution Network Fault Recovery Based on Dynamic Switching Technology 16

Linear Programming Method for Distribution Network Fault Rec...

引用

16th IEEE PES Asia-Pacific Power and Energy Engineering Conference, APPEEC 2024

作者： Zhu, Junpeng Guo, Weijia Dong, Xiaofeng Yuan, Yue College of Electrical and Power Engineering Hohai University Nanjing China Suzhou Power Supply Company State Grid Jiangsu Electric Power Co. Ltd. Suzhou China

ISBN: (纸本)9798350386127

To address the issue of load recovery after blackout in distribution networks, a linear programming method for fault recovery based on dynamic switching technology is proposed. Firstly, an analytical expression elucidating the functional relationship between the adjacency matrix of the network topology and node connectivity is proposed. Based on this, a dynamic model of the network structure is developed to enhance the network reconfiguration strategy. Secondly, considering the dynamic characteristics of non-black start units, a load recovery power adequacy constraint is constructed, and the distribution network fault recovery model is established, which was transformed into a mixed integer linear programming form. Finally, the validity of the islanding strategy is tested based on the optimal scheduling and active and reactive power balance. The effectiveness of this method is validated through a simulation using a 43-bus distribution system example. The results show that the method can effectively coordinates network topology flexibility with distributed resources, hence improving the distribution network's resilience. © 2024 IEEE.

关键词： mixed-integer linear programming

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SCHEDULING JOBS ON A SINGLE STRESS TEST MACHINE IN A RELIABILITY LABORATORY

SCHEDULING JOBS ON A SINGLE STRESS TEST MACHINE IN A RELIABI...

引用

2024 Winter Simulation Conference

作者： Hautz, Jessica Klemmt, Andreas Moench, Lars Kompetenzzentrum Automobil & Ind Elekt GmbH KAI Villach Austria Infineon Technol Dresden GmbH Dresden Germany Univ Hagen Dept Math & Comp Sci Hagen Germany

ISBN: (纸本)9798331534202;9798331534219

We consider a single-machine scheduling problem with unequal job sizes and ready times. Several jobs can be processed at the same time on the machine if the sum of their sizes does not exceed the capacity of the machine. Only jobs of the same family can be processed at the same time. The machine can be interrupted to start a new job or to unload a completed job. A conditioning time is required to reach again the temperature for the stress test. The machine is unavailable during conditioning. Jobs that cannot be completed before conditioning have to continue with processing after the machine is available again. The makespan is to be minimized. A mixed-integer linear program and a constraint programming formulation are established, and a constructive heuristic and a biased random-key genetic algorithm are designed. Computational experiments based on randomly generated problem instances demonstrate that the algorithms perform well.

关键词： mixed-integer linear programming

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A Deep Neural Network Based Method for Predicting Active Transmission Constraints in SCUC 6

A Deep Neural Network Based Method for Predicting Active Tra...

引用

6th International Conference on Power and Energy Technology, ICPET 2024

作者： Haolin, Tang Lin, Chenhui Wu, Wenchuan Yuan, Qihai Department of Electrical Engineering Tsinghua University Beijing China NARI Group Beijing Kedong Power Control System Co. Ltd Beijing China

ISBN: (纸本)9798350375855

Security-Constrained Unit Commitment (SCUC) stands as a critical challenge within power systems. With the continual expansion of power networks, SCUC encounters substantial hurdles in terms of computational time. In practical scenarios, given the imperative of electricity market clearance, this dilemma necessitates frequent resolution throughout the day despite minor alterations in input data. In this study, leveraging machine learning techniques, we present an approach aimed at harnessing previous data effectively to forecast active constraints, thus expediting solutions to the SCUC problem. We introduce a novel methodology for generating training data to predict the active transmission constraint set, ensuring the trained model achieves full prediction coverage. Through extensive computational simulations, our approach demonstrates a remarkable acceleration in computation speed, achieving up to 8 times the efficiency in large-scale scenarios. © 2024 IEEE.

关键词： mixed-integer linear programming

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Learning to Generate Scalable MILP Instances

Learning to Generate Scalable MILP Instances

引用

2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Yang, Tianxing Ye, Huigen Xu, Hua Tsinghua University Beijing China

ISBN: (纸本)9798400704956

Large-scale mixed-integer linear programming (MILP) problems have been efficiently addressed using Machine Learning (ML)-based frameworks, especially ML-based evolutionary optimization frameworks to obtain high-quality solutions. When addressing real-world MILP problems, ML-based evolutionary optimization frameworks often face challenges in acquiring sufficient instances that belong to the same category. This underscores the need for generators that can autonomously produce MILP problems from existing instances. This paper introduces MILPGen, a novel generative framework for autonomous MILP instance generation. Our key contribution lies in the two-stage problem generation in MILPGen: 1) Node Splitting and Merging, which splits the bipartite graph and tries to reconstruct it;2) Scalable Problem Construction, which concatenates tree structures to get larger problems. We demonstrate that the instances generated by MILPGen are highly similar to the original problem instances and can effectively enhance the solution effect of the ML-based evolutionary optimization frameworks. Further experiments show that the scaled-up generated instances still retain the problem's structural properties, validating the proposed framework's effectiveness. © 2024 Copyright held by the owner/author(s).

关键词： mixed-integer linear programming

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Accelerated SCUC Solution: Integrating Cutting Planes, Interior Points, and Rounding Heuristics 5

Accelerated SCUC Solution: Integrating Cutting Planes, Inter...

引用

5th International Conference on Power Engineering, ICPE 2024

作者： Cai, Zhi Hu, Xiaojing Chen, Yanguang Xu, Shengnan Automation Technology China Electric Power Research Institute Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Beijing China Co. Ltd R&Development Department Beijing China

ISBN: (纸本)9798331531140

In this research contribution, we present a novel approach aimed at accelerating online mixed-integer optimization by leveraging heuristic ROUNDING techniques and interior point methods. The cornerstone of our method lies in the construction of a Cardinality cutting plane. This Cardinality cutting plane method effectively harnesses the solution of linear programming (LP) without incorporating the CROSSOVER procedure within the interior point method. It ingeniously forms a feasible area for the segmentation of cutting planes while meticulously configuring the relevant parameters to ensure their viability. Notably, our method seamlessly integrates into any mixed-integer programming (MIP) solver. Our empirical findings decisively demonstrate the superior performance of the proposed algorithm compared to conventional direct solution methods, particularly in terms of its agility in rapidly exploring feasible regions. Additionally, our algorithm exhibits a remarkable acceleration in improving the lower bound. This enhancement significantly enhances the efficiency of solving optimization problems, offering a promising avenue for effectively addressing the complexities of energy system scheduling. © 2024 IEEE.

关键词： mixed-integer linear programming

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Optimizing the Transportation of CO2 Via Vessels in a Milk Run Network of Three Ports 27

Optimizing the Transportation of CO2 Via Vessels in a Milk R...

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27th IEEE International Conference on Intelligent Transportation Systems, ITSC 2024

作者： Gaggero, Mauro Institute of Marine Engineering National Research Council of Italy Genoa16149 Italy GNAMPA-INdAM Gruppo Nazionale per l'Analisi Matematica La Probabilità e le Loro Applicazioni - Istituto Nazionale di Alta Matematica Italy

ISBN: (纸本)9798331505929

The optimization of the transportation of CO2 through ships in a carbon capture and storage context is investigated by means of mixed-integer linear programming and a greedy heuristic approach. The goal is to schedule the berthing and departure times along with the optimal load of vessels carrying CO2 among three different maritime ports, by pursuing the minimization of the usage of temporary storage buffers available at the ports. Since solving the MILP problem can be computationally intensive, a greedy heuristic algorithm based on a threshold mechanism is introduced. This heuristic, with its lower computational requirements, can provide an initial solution to the MILP-based approach, thereby enhancing its performance. Simulation results are presented in two case studies to evaluate the effectiveness of the methods. © 2024 IEEE.

关键词： mixed-integer linear programming

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SOLVING mixed integer linear PROGRAMS BY MONTE CARLO TREE SEARCH

SOLVING MIXED INTEGER LINEAR PROGRAMS BY MONTE CARLO TREE SE...

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2024 Winter Simulation Conference, WSC 2024

作者： Zhang, Gongbo Peng, Yijie PKU-Wuhan Institute for Artificial Intelligence Peking University Wuhan China Guanghua School of Management Peking University Beijing China Xiangjiang Laboratory Changsha China

ISBN: (纸本)9798331534202

mixed integer linear Programs (MILPs) are powerful tools for modeling and solving combinatorial optimization problems. Solving an MILP is NP-hard due to the integrality requirement, and the branch and bound (B&B) algorithm is a widely used exact solution method. In this work, we explore the use of Monte Carlo Tree Search (MCTS) to guide the search within the space composed of branching candidate variables, aiming to efficiently find the optimal solution (if it exists) for an MILP. We adapt the Asymptotically Optimal Allocation for Trees (AOAT) algorithm, a recently proposed MCTS approach in the simulation and optimization field, for solving MILPs. Numerical results demonstrate the potential benefits of the proposed method. © 2024 IEEE.

关键词： mixed-integer linear programming

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MULTI-OBJECTIVE OPTIMIZATION MODELS TO MINIMIZE THE NUMBER OF OPERATORS IN LABOR-INTENSIVE MANUFACTURING CELLS 51

MULTI-OBJECTIVE OPTIMIZATION MODELS TO MINIMIZE THE NUMBER O...

引用

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

作者： Kataoka, T. Morikawa, K. Takahashi, K. Faculty of Engineering Kindai University Hiroshima Japan Graduate School of Engineering Hiroshima University Hiroshima Japan

The advantage of cellular manufacturing (CM) has been widely documented as one of the most resilient production systems in the literature. Generally, the literature has two streams of concepts. One deals with machine-intensive cells and the other with labor-intensive cells. In the field of labor-intensive cells, a hierarchical approach based on two phases has been adopted in many previous papers even though it has some shortcomings. For instance, as the configurations of operators are limited to maximize production rates in phase 1, the total number of operators cannot be decreased for production capacities in phase 2 even if there is a decrease in production rates caused by slack cells. However, it is difficult to solve the problem by integrating the two phases because it is non-linear. Furthermore, it is indispensable for an integrated model in the field of labor-intensive cells to define distinguished operators by "simultaneously considering not only products, operations and cells, but also operators". In this paper, a new integrated mixed integer programming model without phases is proposed and compared with the 2-phase model by toy problems. In addition, considering multi-objective optimization models, the new proposed model is comprehensively compared with the 2-phase model. Firstly, the integrated model based on two phases is redefined by two new decision variables. One is to consider products, operations, cells, and operators simultaneously and the other is to use the cycle time instead of the production rate. Secondly, the proposed model is solved by linearizing the nonlinear equation that multiplies continuous and binary variables. Thirdly, we show some cases where the proposed model leads to fewer operators than the 2-phase model. Finally, we show that the proposed model leads to fewer operators or less unit times than the 2-phase model comprehensively and sustainably. © 2024 Computers and Industrial Engineering. All rights reserved.

关键词： mixed-integer linear programming

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Distributed Generation Curtailment for Maintaining Voltage Stability 13

Distributed Generation Curtailment for Maintaining Voltage S...

引用

13th IEEE Power and Energy Society: Innovative Smart Grid Technologies - Asia, ISGT Asia 2024

作者： Karnib, Nour Graine, Aghyles Grolleau, Emmanuel Bertout, Antoine Gaubert, Jean-Paul Ensma France Université de Poitiers Srd Poitiers France Université de Poitiers Poitiers France

ISBN: (纸本)9798350373929

The progressive integration of distributed generation (DG) gives rise to significant overgeneration within distribution networks. In some cases, it will lead to grid instability and voltage fluctuations, resulting in equipment damage or failures. The goal of this paper is to prevent several impacts of high integration of distributed generation, like grid instability and voltage stabilization challenges. There are several methods aimed at overcoming these impacts to preserve the stability of the network. This paper uses the power curtailment of distributed generation in a dynamic distribution network reconfiguration problem, obtaining a topology with optimized power losses. The novel feature is that only the amount of excess production violating the voltage limits is curtailed. A curtailment model and a relaxed voltage model are presented and can be used for industrial applications. They are tested on a small representative network and a modified IEEE-33 system. © 2024 IEEE.

关键词： mixed-integer linear programming

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Uncertain Decision Making: A Cooperative Agent Model for Flexible Renewable Energy Comunities 59

Uncertain Decision Making: A Cooperative Agent Model for Fle...

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59th International Universities Power Engineering Conference, UPEC 2024

作者： Trevisan, Riccardo Ghiani, Emilio Galici, Marco Pilo, Fabrizio University of Cagliari Dept. of Electrical and Electronic Engineering Cagliari Italy Institute for Research in Technology Comillas Pontifical University Madrid Spain

ISBN: (纸本)9798350379730

The paper proposes an innovative model for integrating energy communities within urban districts according to the smart cities paradigm. The approach developed contemplates the proactive participation of members of an energy community in providing demand-side flexibility to address the variability and non-programmability of renewable energy with the goal of harnessing locally produced energy. A framework for transactive energy has been developed that incorporates forecasting methodologies, uncertainty assessment through Monte Carlo simulations and mixed-integer linear optimization based on cooperative game theory. The effectiveness of the developed model is illustrated through a case study showing resilience and cooperative capabilities in an inherently uncertain decision-making process. © 2024 IEEE.

关键词： mixed-integer linear programming

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