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IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Ren, Yijing Friderikos, Vasilis Kings Coll London Dept Engn Ctr Telecommun Res London WC2R 2LS England

ISBN: (纸本)9781665464833

The emerging beyond fifth-generation (B5G) and envisioned sixth-generation (6G) wireless networks are considered as key enablers in supporting a diversified set of applications for industrial mobile robots (MRs). In this paper, we consider mobile robots that autonomously roam on an industrial floor and perform a variety of tasks at different locations, whilst utilizing high directivity beamformers in millimeter wave (mmWave) small cells for joint communication and sensing. In such scenarios, the potential close proximity of mobile robots connected to different base stations, may cause excessive levels of interference having as a net result a decrease in the overall achievable data rate and service degradation in the network. To mitigate this effect an interference aware path planning algorithm is proposed by explicitly taking into account the achievable performance of both communication and sensing. More specifically, the proposed heuristic scheme aims to find paths with minimal interfering time for each mobile robot whilst improving the overall communication and sensing performance. A wide set of numerical investigations reveal that the proposed heuristic path planning scheme for the mmWave connected mobile robots can improve the overall achievable communication throughput and the sensing mutual information by up to 35.6% and 23.6% respectively compared to an interference oblivious scheme. Most importantly, those gains are attained without penalizing noticeably the total travel time of the MRs.

关键词： Beyond 5G Beamforming Industry 4.0 joint communication and sensing mobile robots mixed integer linear programming path planning

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A multi-product dynamic supply chain inventory model with supplier selection, joint replenishment, and transportation cost

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ANNALS OF OPERATIONS RESEARCH 2022年第2期316卷 729-762页

作者： Ventura, Jose A. Golany, Boaz Mendoza, Abraham Li, Chenxi Penn State Univ Harold & Inge Marcus Dept Ind & Mfg Engn University Pk PA 16802 USA Technion Israel Inst Technol William Davidson Fac Ind Engn & Management IL-32000 Haifa Israel Univ Panamer Fac Ingn Alvaro Portillo 49 Zapopan 45010 Jalisco Mexico

The aim of this paper is to solve a multi-period supplier selection and inventory lot-sizing problem with multiple products in a serial supply chain. Compared to previous models proposed in the literature, our research incorporates a richer cost structure involving joint replenishment costs for raw material replenishment and production, and a more realistic description of the transportation costs represented as a vector of full-truck load costs for different size trucks. This problem can be displayed graphically as a time-expanded transshipment network defined by nodes and arcs that can be reached by feasible material flows. First, we propose an integrated mixed integer linear programming model that minimizes the cost over the entire supply chain for a given planning horizon. The model determines the optimal dynamic supplier selection, inventory lot-sizing, and production schedule simultaneously. Second, a sequential approach is proposed to solve the same problem. That is, a production schedule is determined first, and then a supplier selection and replenishment strategy is obtained according to that predetermined schedule. Sensitivity analysis comparing the two approaches is performed. Results show that, even though the integrated approach achieves the minimum cost, the sequential approach may be suitable for solving large-scale instances of the problem as it requires less information sharing and generates a near-optimal solution with shorter implementation time and computational effort.

关键词： Supply chain management Production planning Multiple products Time-varying demand Supplier selection mixed integer linear programming

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A study on photovoltaic charging strategy of electric vehicles with multi-objective constraints

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2022年第3期40卷 231-238页

作者： Wu, Haowen Wang, Chong Zhou, Yudi Xie, Wenwang Chen, Chen Southern Power Grid Digital Grid Res Inst Guangzhou Guangdong Peoples R China Hefei Univ Technol Hefei Anhui Peoples R China

Installation of photovoltaic panels (PV) in a workplace for charging electric vehicles (EV) can help in both clean energy and ease of life. The disorderly charging behaviour of an EV photovoltaic charging station will aggravate the fluctuation of power grid distribution, and potentially affects the energy dispatching among electric vehicles, photovoltaic power generation and increasing cost. In order to solve these problems, we propose a photovoltaic charging strategy under multi-objective constraints. Taking the photovoltaic charging scene of electric vehicles, charging power and charging time of electric vehicles into account, the proposed solution can be formulated as a mixed integer linear programming task with multi-objective constraints. A wise charging strategy of electric vehicles is given by solving the formulated integer linear programming problem. Simulation results indicate that our proposed method is effective and useful to reducing charging cost.

关键词： electric vehicle charging photovoltaic power generation multi objective constraints hardware-in-the-loop mixed integer linear programming

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Optimal Battery Energy Storage Dispatch in Energy and Frequency Regulation Markets While Peak Shaving an EV Fast Charging Station

IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY

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IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY 2022年 9卷 374-385页

作者： Argiolas, Luca Stecca, Marco Ramirez-Elizondo, Laura M. Soeiro, Thiago Batista Bauer, Pavol Delft Univ Technol Elect Sustainable Energy Dept NL-2628 CD Delft Netherlands

Battery Energy Storage Systems typically procure their primary revenues from regulated energy and ancillary services markets;nonetheless, they have great potential in supporting distribution network operators and their users. This paper evaluates the potential business case of battery storage systems integrating market application and services to a photovoltaic assisted electric vehicle fast-charging station. A mathematical deterministic optimization problem is formulated using mixed-integer linear programming to combine battery storage system operation in the day-ahead and frequency regulation market and the remunerated services offered to the charging station. The technical and economic feasibility of the solution and the applicability of the proposed framework is verified through a case study reflecting an existing photovoltaic assisted charging station in the Netherlands and considering the Dutch energy market framework and prices. The study shows that such battery storage system implementation is economically and technically advantageous for the players involved. The battery storage system can stack additional revenues on top of the market revenues. The charging station benefits from a reduced peak power and a 30% tariff reduction, and the system operator would indirectly benefit from the shaved charging station profile. Furthermore, the analysis shows that providing services to the charging station from the battery storage system does not significantly impact its market-related revenues.

关键词： Battery energy storage system day ahead market distribution network electric vehicle fast charging station financial analysis mixed integer linear programming primary frequency regulation

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An improved LINMAP for multicriteria decision: designing customized incentive portfolios in an organization

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OPERATIONAL RESEARCH 2022年第4期22卷 3489-3520页

作者： Rubiano-Moreno, Jessica Nucamendi-Guillen, Samuel Cordero-Franco, Alvaro Rodriguez-Magana, Alejandro Univ Ciencias Aplicadas & Ambientales Fac Ciencias Adm & Comerciales Calle 222 55-37 Bogota Colombia Univ Panamer Fac Ingn Alvaro Portillo 49 Zapopan 45010 Jalisco Mexico Univ Autonoma Nuevo Leon Fac Ciencias Fis Matemat Av Univ S-N San Nicolas De Los Garza 66451 Nuevo Leon Mexico Univ Panamer Escuela Ciencias Econ & Empresariales Alvaro Portillo 49 Zapopan Jalisco Mexico

This study proposes three new versions of the well-known linear programming technique for multidimensional preference analysis (LINMAP). LINMAP addresses the multi-criteria decision problem by analyzing individual differences in preferences in relation to a set of prespecified incentives in multidimensional attribute space. The proposed models satisfy the decision-maker's specific needs, such as determining a fixed number of incentives to be active or assigning a minimum/maximum weight for the active incentives. The performance of the developed models is assessed using information from a case study in which a decision-maker desires to determine an optimal portfolio of incentives based on the preferences of individuals surveyed. Experimental results confirm that the proposed models could obtain solutions according to the decision-maker's needs, yielding a better selection of incentives to activate and their corresponding distribution of the weights than those of the original LINMAP model. Moreover, the consistency of the proposed models is evaluated by performing a sensitivity analysis over database variations of the case study and comparing the outcomes with the results provided in the original case study. Overall, this work is promising when creating a design portfolio, considering individuals' different preferences.

关键词： Data analysis Incentive LINMAP mixed integer linear programming Multicriteria decision making

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MILP performance improvement strategies for short-term batch production scheduling: a chemical industry use case

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SN APPLIED SCIENCES 2022年第4期4卷 87页

作者： Kunath, Sascha Kuehn, Mathias Voelker, Michael Schmidt, Thorsten Ruehl, Phillip Heidel, Gennadij Tech Univ Dresden Chair Mat Handling D-01062 Dresden Germany BASF Schwarzheide GmbH D-01987 Schwarzheide Germany

This paper presents the development and mathematical implementation of a production scheduling model utilizing mixed-integer linear programming (MILP). A simplified model of a real-world multi-product batch plant constitutes the basis. The paper shows practical extensions to the model, resulting in a digital twin of the plant. Apart from sequential arrangement, the final model contains maintenance periods, campaign planning and storage constraints to a limited extend. To tackle weak computational performance and missing model features, a condensed mathematical formulation is introduced at first. After stating that these measures do not suffice for applicability in a restrained time period, a novel solution strategy is proposed. The overall non-iterative algorithm comprises a multi-step decomposition approach, which starts with a reduced scope and incrementally complements the schedule in multiple subproblem stages. Each of those optimizations holds less decision variables and makes use of warmstart information obtained from the predecessor model. That way, a first feasible solution accelerates the subsequent improvement process. Furthermore, the optimization focus can be shifted beneficially leveraging the Gurobi solver parameters. Findings suggest that correlation may exist between certain characteristics of the scheduling scope and ideal parameter settings, which yield potential for further investigation. Another promising area for future research addresses the concurrent multi-processing of independent MILPs on a single machine. First observations indicate that significant performance gains can be achieved in some cases, though sound dependencies were not discovered yet.

关键词： mixed integer linear programming Batch scheduling Multi-product plant Multi-stage Parallel units MILP performance Makespan minimization Chemical industry Gurobi

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A matheuristic for passenger service optimization through timetabling with free passenger route choice

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OR SPECTRUM 2022年第4期44卷 1087-1129页

作者： Fonseca, Joao Paiva Zuendorf, Tobias van der Hurk, Evelien Zhu, Yongqiu Larsen, Allan DTU Management Akad VejDTU Bldg 358 DK-2800 Lyngby Denmark Karlsruhe Inst Technol Inst Theoret Informat Kaiserstr 12 D-76131 Karlsruhe Germany DTU Management BygningstorvetDTU Bldg 116 DK-2800 Lyngby Denmark

Designing a public transport timetable that maximizes passenger service, measured in weighted travel time, is an intricate problem. The weighted travel time depends on the free route choice of passengers. Passenger route choice depends on the timetable. In turn, the timetable that minimizes weighted travel time depends on the route choice of passengers-and therefore requires passenger route choice information. Consequently, a sequential approach where timetables are designed provided pre-fixed passenger assignment to routes may not find the optimal timetable. This paper aims to integrate passenger route choice and timetabling. It addresses the problem of designing maximal passenger service public transport timetables in systems with free route choice within a budget for operating costs. Operating costs are defined by the minimal cost vehicle schedule required to operate the timetable. The proposed methodology integrates a matheuristic for timetabling and vehicle scheduling with a passenger assignment model in an iterative framework, where different forms of integration are evaluated. Focus is on long- to medium-term timetabling, provided an initial timetable. The results for a realistic case study in the Greater Copenhagen area indicate that our approach consistently leads, at no additional cost, to timetables that represent a reduction in passenger weighted travel time in comparison with both an initial timetable and a non-integrated timetabling method that receives a single-passenger assignment as input.

关键词： Public transport Bus timetabling Passenger route choice mixed integer linear programming Matheuristic

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Efficient IoT Devices Deployment Using Branch and Bound Method 14

Efficient IoT Devices Deployment Using Branch and Bound Meth...

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Kim, Haesik Vtt Technical Research Centre of Finland P.O. Box 1100 OuluFI-90570 Finland

ISBN: (纸本)9798350313277

The Internet Of Thing (IoT) networks are widely investigated in 5G system and will be still a key technical system to drive massive connectivity of 6G systems. As the IoT devices and networks are getting smarter, the IoT ecosystem allows us to bridge between human life and digital life and accelerate the transition towards a hyper-connected world. Optimal and scalable IoT network design has been investigated in many research groups but key challenges in this topic still remain. In this paper, we investigate IoT devices deployment problem to minimize the transmission and computation cost among network nodes. We formulate the IoT devices deployment problem as mixed-integer Nonlinear programming (MILNP) problem. After relaxing the constraints and transforming the problem to a mixed integer linear programming (MILP) problem, we propose a new branch and bound (BB) method with a machine learning function and solve the MILP problem. In the numerical analysis, we evaluate both conventional BB method and the proposed BB method with weighting factors and compare the objective function values, the number of explored nodes, and computational time. The performances of the proposed BB method are significantly improved under the given simulation configuration. We find the optimal mapping of IoT devices to fusion nodes. © 2023 IEEE.

关键词： 6G Branch and Bound method etc IoT Machine learning mixed integer linear programming

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linear Approximation of Calendar Battery Aging Costs for MILP-Based Power Dispatch Optimization

Linear Approximation of Calendar Battery Aging Costs for MIL...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Majewski, Kurt Seydenschwanz, Martin Gottschalk, Corinna Weiland, Sonja Siemens AG T DAI ORD-DE Germany Technische Universität München Munich Germany

ISBN: (纸本)9798350396782

Batteries should be operated such that benefits and associated chemical aging detriments are balanced. We present a mixed-integer linear approximation for the cost of calendar aging of batteries taking temperature and state of charge into account. An example with calendar and cyclic aging costs shows that the revenue from the operation of a battery can be increased by integrating aging costs into a model predictive control optimization. © 2023 IEEE.

关键词： battery aging battery management systems mathematical programming mixed integer linear programming piecewise linear approximation

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A Dispatching Method for Pumped Storage Power Station Group with Load Smoothness as the Goal 3

A Dispatching Method for Pumped Storage Power Station Group ...

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3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Chen, Wendong Wu, Fangrong Chen, Gengwei Zou, Bin China Huadian Corporation Ltd. Fujian Company Fuzhou China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798350318180

This paper proposes a scheduling method for pumped storage power stations based on the smoothness of the comprehensive load, which uses the difference between the maximum and minimum load levels of the residual load to measure the smoothness of the load, and constructs a daily scheduling model for a pumped storage power station group. The method proposed in this paper avoids the difficulty of considering the operation of thermal power units in conventional hydroelectric coordinated pumped storage scheduling models, which greatly increases the computational complexity of the model. This method also avoids the difficulty of reflecting the independent operation of each province in the coordination of thermal power in the case of shared pumped storage power stations across multiple provinces. Due to the linear representation of the residual load used in the load smoothness index, the model is a mixed integer programming model, which allows for a more detailed description of the operational constraints of pumped storage power plants. This makes the model's solving speed faster and more in line with the improvement of the residual load smoothness through peak shaving and valley filling. The characteristics of the method proposed in this paper were verified through testing based on the IEEE RTS system and actual data from East China Power Grid. © 2023 IEEE.

关键词： dispatch Load smoothness index mixed integer linear programming peak load shifting pumped storage power station

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