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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Kuribayashi, Yusuke Sowa, Sotaro Takeshita, Keisuke Yamazaki, Kimitoshi Shinshu University Graduate School of Engineering Wakasato 4-17-1 Nagano Nagano Japan Toyota Motor Cooperation Japan Shinshu University Faculty of Engineering Wakasato 4-17-1 Nagano Nagano Japan

ISBN: (纸本)9798331531614

This paper describes a method for solving task planning and motion planning problems simultaneously. We target a fetch-and-carry of a small item by a single-arm mobile manipulator and introduce a method that can generate a sequence of actions and motions required for each action, even in environments with narrow open spaces such as corridors. In addition, to deal with a case where another object is already placed at the target location, we introduce a push-aside action and extend the previous method to include this action. As our method is formulated using mixed integer linear programming (MILP), the calculation time is relatively short, irrespective of the complexity of the target problem. To verify the efficiency of the proposed method, we performed a quantitative evaluation through simulation and conducted experiments on an actual mobile manipulator to verify feasibility of the methods. © 2025 IEEE.

关键词： mixed-integer linear programming

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A New Planning Model for Optimal Feeder Routing of Radial Distribution System Using mixed integer linear programming Technique 25

A New Planning Model for Optimal Feeder Routing of Radial Di...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Shazly, Shazly Ahmed Mahmoud, Hassan Mohamed Albags, Mohamed Shibl Elzawawy, Ahmed Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Benha13511 Egypt Nahda University Faculty of Engineering Department of Electrical Engineering Beni Suef62511 Egypt

ISBN: (纸本)9798350379648

Several studies have been focused on developing the distribution system planning techniques, varying from classical to nontraditional soft computing techniques, to solve the distribution system planning problem. This paper presents a new planning model for accurate mathematical planning to get optimum feeder routing of radial distribution systems using a mixed integer linear programming (MILP) technique. The model treats the loads at different load buses as injected power. The model also considers the ohmic power loss of various branches as a variable for optimization. All cost items (capital cost, energy loss cost, cost of bays, and line interruption cost) are considered. Also, bus voltage and line capacity limits are considered in addition to the different line sizes. Model verification has been made using two test examples. Lingo software is used to verify the proposed planning model. The developed model can be extended to deal with the general distribution planning problem in which both feeding substations and feeders can be optimized. In addition, it is very important for getting the optimal feeder routing of the system. © 2024 IEEE.

关键词： mixed-integer linear programming

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Fast Topology Identification of AC / DC Hybrid Distribution Network Based on mixed integer linear programming 2

Fast Topology Identification of AC / DC Hybrid Distribution ...

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2nd International Conference on Cyber-Energy Systems and Intelligent Energy, ICCSIE 2024

作者： Hu, Shiyao Feng, Xichun Kang, Xiaofan Ju, Yuntao Jiang, Jing Economic and Technical Research Institute State Grid Hebei Electric Power Co. Ltd Shijiazhuang China School of Electrical and Control Engineering North China University of Technology Beijing China State Grid Economic and Technological Research Institute Co. Ltd Beijing China

ISBN: (纸本)9798350373318

Topology identification is crucial for advanced analysis such as state estimation in hybrid AC/DC distribution networks. Traditional topology identification methods based on data statistics lack accuracy, and optimization-based methods exhibit low efficiency. To address these issues, a topology identification method based on mixed-integer linear programming is proposed. Initially, the normalized Lagrange multiplier is utilized to identify suspicious measurements, forming a set of suspicious measurements to reduce the number of integer variables to be determined. Subsequently, a linearization method for network constraints in hybrid AC/DC distribution networks is introduced to transform the topology identification problem into a mixed-integer linear programming model. The simulation results demonstrate that by constructing a set of suspicious measurements and linearizing network constraints, the efficiency of solving the problem is significantly improved while ensuring the accuracy of identification. © 2024 IEEE.

关键词： mixed-integer linear programming

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A mixed integer linear programming based optimal operational and sizing approach for a Hybrid Local Microgrid

A Mixed Integer Linear Programming based optimal operational...

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2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Hossain, Mohammad Shafayet Iftekhar Bin Ashraf, Mohammad Ahmed, Saif University of Lorraine Department of Energy France North South University Department of Electrical and Computer Engineering Bangladesh

ISBN: (纸本)9798331529765

Optimal sizing of microgrids is achieving higher importance in the current era of energy transition driven by renewable sources. Due to the intermittence of the renewable sources i.e. PV, wind assisted by energy storages i.e. battery the optimal sizing of the microgrids alonf with cost minimization is a great challenge. This study presents a methodological framework for determining the optimal configuration of a hybrid microgrid, integrating various energy resources such as photovoltaic (PV) generation, battery storage, a genset, and grid interconnection. Employing Pyomo optimization tool with a mixed-integer linear programming algorithm, the research focuses on sizing components within a 20 kW PV microgrid. Through meticulous examination of load demand and installed PV capacity, the algorithm strategically optimizes the sizing of PV panels, batteries, gensets, and grid interactions to minimize both capital expenditure (CAPEX) and operational expenditure (OPEX). The microgrid's performance is analyzed under three pricing schemes: net metering, selling excess energy to the grid (selling price less than buying price), and giving it away (zero price). Additionally, in off-grid mode, the total CO2 emissions are minimized. The proposed methodology offers a systematic approach for designing economically viable and efficient hybrid microgrids, essential for sustainable energy systems. © 2024 IEEE.

关键词： mixed-integer linear programming

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mixed-integer linear programming Models for One-Commodity Pickup and Delivery Traveling Salesman Problems 6th

Mixed-Integer Linear Programming Models for One-Commodity Pi...

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6th Workshop on Engineering Applications (WEA)

作者： Palacio, Juan D. Carlos Rivera, Juan Univ EAFIT Escuela Ciencias Dept Ciencias Matemat Grp Invest Modelado Matemat Medellin Colombia

ISBN: (纸本)9783030310196;9783030310189

This article addresses two different pickup and delivery routing problems. In the first one, called the one-commodity pickup and delivery traveling salesman problem, a known amount of a single product is supplied or demanded by a set of two different types of locations (pickup or delivery nodes). Therefore, a capacitated vehicle must visit each location once at a minimum cost. We also deal with the relaxed case where locations can be visited several times. In the last problem, the pickup or delivery operation can be split into several smaller pickups or deliveries, and also locations can be used as temporal storage points with the aim of reducing the cost of the route. To solve these problems, we present two mixed-integer linear programming models and we solve them via commercial solver. We analyze how several visits to a single location may improve solution quality and we also show that our simple strategy has a good performance for instances with up to 60 locations.

关键词： Pickup and delivery Traveling salesman problem mixed-integer linear programming Split delivery

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Optimal Sensor Placement and Battery Pack Configuration in Electrochemical Energy Storage Systems: A mixed-integer Non-linear programming Approach 3

Optimal Sensor Placement and Battery Pack Configuration in E...

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3rd International Conference on Computing, Communication, Perception and Quantum Technology, CCPQT 2024

作者： Wei, Shibo Jiang, Liping Zhang, Xiaojun Zhang, Jingwen Tian Di Technology Co. Ltd. CCTEG Beijing Technology Research Branch Beijing100013 China Xiaoshan District Fire Rescue Brigade Hangzhou311201 China West Lake Scenic Area Fire Rescue Brigade Hangzhou311607 China Chinese Institute of Coal Science CCTEG Beijing100013 China

ISBN: (纸本)9798331528386

The integration of electrochemical energy storage (EES) systems in diverse applications from portable devices to grid storage is crucial for the transition to sustainable energy sources. Efficient battery management is vital for optimizing performance and ensuring safety, with a focus on the strategic placement of sensors and battery pack configuration. This paper introduces a mixed-integer nonlinear programming (MINLP) model that optimizes these aspects by considering three-dimensional spatial configurations and diverse battery types. The model aims to minimize costs while ensuring comprehensive coverage and stringent safety standards. It extends beyond traditional methods by incorporating adaptive strategies that enhance predictive capabilities and operational efficiency. By applying this model in detailed case studies, the paper demonstrates significant improvements in cost efficiency and system reliability, offering a robust framework for enhancing battery management systems in various technological and operational settings. This approach not only addresses current challenges but also adapts to dynamic conditions, highlighting its potential to significantly impact the future of energy storage solutions. © 2024 IEEE.

关键词： mixed-integer linear programming

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Automated reinforcement trim waste optimization in RC frame structures using building information modeling and mixed-integer linear programming

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AUTOMATION IN CONSTRUCTION 2021年 124卷 103599-103599页

作者： Khondoker, Md. Tareq Hossain Khulna Univ Engn & Technol Dept Bldg Engn & Construct Management Khulna 9203 Bangladesh

Construction of RC frame requires a considerable amount of reinforcement steel bars. Shaping market length rebars to get design lengths leads to the production of waste. The purpose of this research is to optimize the use of available market length rebars in such a way that will generate the least possible waste. Accordingly, Building Information Modeling (BIM) based automated framework integrated with mixed-integer linear programming (MILP) has been presented in this article. This methodology involves extracting reinforcement detailing data automatically during the design phase using BIM. Then, implementing the column generation algorithm to generate only necessary cutting patterns. Then, optimizing the use of market length rebars by applying the MILP approach. An RC frame of a three-storied building has been analyzed to evaluate the efficiency of the proposed framework. The results show that a substantial amount of trim waste reduction can be achieved quickly and efficiently by the suggested method.

关键词： Building information modeling mixed-integer linear programming Trim waste Optimization Reinforcement steel bars

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mixed-integer linear programming Models for Coordinated Train Timetabling with Dynamic Demand

Mixed-Integer Linear Programming Models for Coordinated Trai...

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IEEE Intelligent Transportation Systems Conference (IEEE-ITSC)

作者： Yin, Jiateng Andrea, D'Ariano Wang, Yihui Xun, Jing Su, Shuai Tang, Tao Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Roma Tre Univ Dept Engn Rome Italy

ISBN: (纸本)9781538670248

In this paper, we study the optimization of coordinated train timetable in an urban rail network under the consideration of time-dependent passenger demands. This problem arises in large urban rail networks with multiple lines that the passengers may transfer among different lines to arrive at their destinations. We propose an exact formulation to generate the optimal train timetables of all the involved lines in a rail transit network synchronously, and our objective is to minimize the maximal level of crowdedness of stations. In particular, we introduce several sets of passenger flow variables that enable to model this complex problem as a mixed-integer linear programming (MILP) that is possible to be solved to the optimal solution. By considering the number of boarding and alighting passengers as passenger flow variables, we explicitly incorporates the number of in-vehicle passengers in the modelling framework to capture the train carrying capacity constraints. The formulated models first extend the passenger-oriented train timetabling models in existing literature from a single transit line to a whole connected network. Case studies are conducted to verify the effectiveness of the proposed model.

关键词： Coordinated train timetabling Rail transit network mixed-integer linear programming

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A comparison between mixed-integer linear programming and dynamic programming with state prediction as novelty for solving unit commitment

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 125卷 106426-106426页

作者： Putz, Dominik Schwabeneder, Daniel Auer, Hans Fina, Bernadette Tech Univ Wien Energy Econ Grp EEG Gusshausstr 25-29E370-3 A-1040 Vienna Austria Siemens AG Austria Siemensstr 90 A-1210 Vienna Austria AIT Austrian Inst Technol Giefinggasse 4 A-1210 Vienna Austria

Recently, the increasing prevalence of renewable energies has faced the challenge of operating power supply systems to efficiently plan electricity generation on a daily basis, since renewable energies are generated intermittently and the decisions of the individual generation units are discrete. The Unit Commitment (UC) problem, which determines the dispatch of generation units, is one of the critical problems in the operation of power supply systems. A long list of formulation proposals have been made that claim to solve this problem. For this purpose, two established approaches, mixed-integer linear programming (MILP) and backward dynamic programming (DP), are used as basis for a deterministic single-generator unit with general convex cost function in this paper. The DP algorithm is enhanced by a so-called state prediction, which reduces the time to find the optimal solution. The proposed formulation is tested empirically on the basis of existing formulations at long term profit based UC instance derived from real data. Finally, the calculation results show that the derived approach significantly shortens the computation time, which confirms the effectiveness of state prediction. The comparison of the approaches shows that the DP algorithm with state prediction delivers a satisfying solution in significantly less time than DP and MILP. Furthermore, the given linearity of the dependence of the computation time on number of steps is a superior advantage of the DP strategy. This superiority becomes even more evident when the planning horizon extends over a longer period of time.

关键词： Unit commitment Optimisation approach mixed-integer linear programming Dynamic programming Prediction algorithms State optimisation

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A mixed-integer linear programming model for multiechelon and multimodal supply chain system considering carbon emission

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COGENT ENGINEERING 2022年第1期9卷 Article: 2044589页

作者： Ardliana, Thina Pujawan, I. Nyoman Siswanto, Nurhadi Shipbldg Inst Polthechn Dept Design & Manufacture Surabaya Indonesia Sepuluh Nopember Inst Technol Dept Ind Engn Surabaya Indonesia

Considering carbon emissions when making supply chain decisions has been an essential contributor for keeping this world more sustainable. This paper presents a mixed-integer linear programming (MILP) model to optimize production and transportation decision where the transportation activities involve a multimodal combination. The proposed mathematical model was aimed at minimizing the total costs incurred from supply chain activities as well as the emissions generated. Carbon cap is used to ensure that the emissions produced in the whole activities do not exceed the allowable limit. In this research, we address a multi-product, multi-plant, multi-departure, and arrival stations where multiple customers are to be served for multiple periods. The numerical tests show that the demand, carbon tax, and distance significantly affected the total emissions and the total costs. Interestingly, we observed that the decisions are much more affected by the logistical costs rather than the emission costs. The model presented in this paper can assist the decision makers to make production, delivery, and inventory decisions when multi-modal transportation is involved.

关键词： Supply chain system multimodal mixed-integer linear programming carbon emission

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