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2024 International Annual Conference of the Italian Association of Electrotechnics

作者： Cometa, Roberto Velini, Angelo Lorusso, Francesco Ricca, Antonio Shrizzai, Roberto Bruno, Sergio Politecn Bari Dept Elect & Informat Eng DEI Bari Italy Dept Energy Technol & Renewable Sources ENEA Portici Italy

ISBN: (纸本)9798350378498;9788887237627

The paper presents the structure of an open-source software tool that can solve an Optimal Network Reconfiguration problem for a distribution grid. The problem includes kinship constraints that permit to fully represent the logics which are behind the principal distribution automation schemes adopted by Distributor System Operators to deal with the fault detection, isolation and recovery function. The algorithm is structured to be fully open-source and it is developed on a Python-based environment. The adopted network models are also open-source and based on the Open-DSS software. Results obtained on the model of a realistically sized MV primary distribution network are shown.

关键词： Distribution Automation FDIR mixed-integer linear programming Protection Coordination Reconfiguration Problem

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Online Multi-appointment scheduling under Demand for Oncology Patient Treatment 10

Online Multi-appointment scheduling under Demand for Oncolog...

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10th International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Fredes, Macarena Davila, Sebastian Quezada, Franco Univ Santiago Chile USACH Ind Engn Dept MSc Ind Engn MCII Program Santiago Chile Univ Santiago Chile USACH Ind Engn Dept Santiago Chile Lab Dev Sustainable Prod Syst LDSPS Santiago Chile

ISBN: (纸本)9798350373981;9798350373974

This research is dedicated to formulating a practical problem related to the assignment of oncology clinic routes. The objective is to schedule medical events for patients attending health centers, taking into account the variable demand and limited resources in this field. To achieve this, three types of solutions are considered. The first is an Online Scheduling Algorithm, which simulates a scheduling process based on medical routes and also includes its inverse version. The next is a mixed-integer linear programming (MILP) model. In this case, information is centralized, and patients are scheduled based on their requirements, minimizing delays in their appointments and/or medical treatments. These methodologies are compared with the current mode of assignment used. To test the previously proposed solutions, data provided by the Arturo Lopez Perez Foundation (FALP) will be used.

关键词： mixed-integer linear programming

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An innovative modelling framework for freight consolidation in transportation planning

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IIMB MANAGEMENT REVIEW 2025年第1期37卷

作者： Kumar, Manoj Anoop, K. P. Natl Inst Technol Jalandhar Dept Math & Comp Jalandhar Punjab India Natl Inst Technol Calicut Dept Mech Engn Calicut Kerala India

This paper addresses freight consolidation in rail transportation planning. Multiple demand destinations are served in a single trip to utilise the volume discount on freight rate. An efficient mixed-integer linear programming (MILP) based modelling framework is proposed to optimally allocate rail wagons to a given set of destinations considering the shipment options offered by Indian Railways. Twelve problem instances are derived using real data from an Indian food grain organisation and are solved to optimum using the CPLEX solver in quick time. The results indicate that multi-point orders can reduce the total transportation cost and ease the handling of shipments at terminals. (c) 2025 Published by Elsevier Ltd on behalf of Indian Institute of Management Bangalore. This is an open access article under the CC BY-NC-ND license (http://***/licenses/ by-nc-nd/4.0/)

关键词： Freight consolidation Rail freight transportation mixed-integer linear programming Indian Railways Milk run logistics

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Collision-free trajectory planning for drones with velocity dependent energy consumption and moving piggyback vehicles

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OR SPECTRUM 2025年 1-48页

作者： Kimms, Alf Muench, Christin Univ Duisburg Essen Mercator Sch Management Lotharstr 65 D-47048 Duisburg Germany

In this work, we challenge the common assumption in truck-drone last-mile delivery that trucks and drones operate on a graph. Instead, we adopt a geometric approach, allowing the vehicles to operate in Euclidean space. Our proposed mixed-integer linear program determines a collision-free trajectory for a drone in the Euclidean space with obstacles, where the drone is launched and recovered by moving vehicles. Compared to graph-based approaches, the advantages are: (a) Flexible launching and recovery: The drone can be launched and recovered from any position along the streets, rather than being limited to discrete points (i.e., nodes of a graph). (b) Continuous drone velocity: The drone velocity is a continuous variable, and the drone energy consumption depends directly on its velocity. (c) No-fly zones and obstacles: Trajectory planning is incorporated to ensure a collision-free flight (rather than considering detours as a predefined parameter). To the best of our knowledge, such a geometric approach is new in truck-drone last-mile delivery. In our computational study we prove the usefulness of our geometric approach, as even large instances with up to 300 obstacles can be solved within reasonable computation time. In comparison to graph-based approaches, our geometric approach yields faster delivery times and enables the drone to reach customers that are out of its reach in graph-based approaches.

关键词： Last-mile delivery Drones Trajectory planning Piggyback vehicles mixed-integer linear programming

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Robustness Verification of Multi-label Neural Network Classifiers 31st

Robustness Verification of Multi-label Neural Network Classi...

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31st International Static Analysis Symposium

作者： Mour, Julian Drachsler-Cohen, Dana Technion Haifa Israel

ISBN: (纸本)9783031747755;9783031747762

Multi-label neural networks are important in various tasks, including safety-critical tasks. Several works show that these networks are susceptible to adversarial attacks, which can remove a target label from the predicted label list or add a target label to this list. To date, no deterministic verifier determines the list of labels for which a multilabel neural network is locally robust. The main challenge is that the complexity of the analysis increases by a factor exponential in the multiplication of the number of labels and the number of predicted labels. We propose MuLLoC, a sound and complete robustness verifier for multi-label image classifiers that determines the robust labels in a given neighborhood of inputs. To scale the analysis, MuLLoC relies on fast optimistic queries to the network or to a constraint solver. Its queries include sampling and pair-wise relation analysis via numerical optimization and mixed-integer linear programming (MILP). For the remaining unclassified labels, MuLLoC performs an exact analysis by a novel mixed-integer programming (MIP) encoding for multi-label classifiers. We evaluate MuLLoC on convolutional networks for three multi-label image datasets. Our results show that MuLLoC classifies all labels as robust or not within 23.22 min on average and that our fast optimistic queries classify 96.84% of the labels.

关键词： mixed-integer linear programming

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Mobility-aware optimal trade planning and mean field game-based decentralized charging control for large-scale electric vehicles

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ASIAN JOURNAL OF CONTROL 2024年第2期26卷 598-616页

作者： Xu, Fuguo Zhao, Kai Fu, Qiaobin Chiba Univ Grad Sch Engn Chiba Japan Sophia Univ Dept Engn & Appl Sci Tokyo Japan Harbin Engn Univ Coll Math Sci Harbin Peoples R China Chiba Univ Grad Sch Engn 1-33 Yayoicho Chiba 2638522 Japan

The uncertainty mobility characteristics of electric vehicles (EVs) are a key factor that influence the charging station trade income with the power grid. In this paper, a hierarchical energy management strategy is proposed for charging stations when large-scale EVs are considered. The traveling and parking mobility characteristics of EVs are first extracted by analyzing historical real-world traveling data. Then, a day-ahead power trade planning strategy between the grid and charging station to maximize incomes is developed by solving a mixed-integer linear programming problem. Furthermore, based on EV mobility characteristics, clusters are generated to classify different parking behaviors, where a mean field game-based decentralized charging control scheme for individual EVs in each cluster is employed. The target of the proposed optimal charging controller is to guarantee the charging power tracking performance and the power demand of individual EV at the terminal time for subsequent travel. Finally, simulations on MATLAB/Simulink platform are conducted to show the effectiveness of the proposed hierarchical energy management strategy.

关键词： decentralized control large-scale EVs mean field game mixed-integer linear programming power trade planning real-time charging control

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Analysing sector coupling technologies for Re-purposing coal-fired power plants-Case study for the ENTSO-E grid

IET ENERGY SYSTEMS INTEGRATION

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IET ENERGY SYSTEMS INTEGRATION 2023年第1期5卷 95-118页

作者： Traupmann, Anna Greiml, Matthias Steinegger, Josef Kuehberger, Lisa Kienberger, Thomas Univ Leoben Chair Energy Network Technol Leoben Austria

The high emission intensity of coal-fired power plants (CFPP) leads to the inevitable next step towards energy transition, the coal phase-out. One challenge is the subsequent use of still-functioning assets. Re-purposing these assets avoids value loss and creates new opportunities for coal regions. Therefore, this study considers the sector coupling technologies Power-to-Gas (PtG) and Gas-to-Power (GtP) as re-purposing options. First, a multi-variable mixed-integer linear programming optimisation model is established. This model includes the participation of the plant in the current (2020) and future (2030, 2040) electricity and natural gas spot-markets and the balancing power market while fulfilling existing contracts, and allows for determining the re-purposing technologies' operating profiles. By applying a techno-economic analysis, investment recovery periods of the considered re-purposing technologies are assessed, which range between two (GtP) and over ten (PtG) years. A sensitivity analysis accounting for current energy prices and technological advancements reveals capital expenditure has the highest impact on this Return-On-Investment period. Additionally, a case study considering the Austrian energy grids is performed to account for the grid impact of integrating these technologies at former CFPP sites. Thus, it is found that the investigated sector coupling technologies have the potential to compensate for grid congestions even in profit-optimised operation.

关键词： coal phase-out combined cycle gas turbine energy markets mixed-integer linear programming power-to-gas

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Detailed scheduling of forest harvesting at the operational level incorporating decisions on multiple machine assignment

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INTERNATIONAL JOURNAL OF FOREST ENGINEERING 2023年第3期34卷 353-365页

作者： Arora, Rohit Sowlati, Taraneh Mortyn, Joel Univ British Columbia Dept Wood Sci Ind Engn Res Grp Vancouver BC V6T 1Z4 Canada Western Forest Prod Inventory & Anal Vancouver BC Canada

It is crucial to efficiently schedule harvesting activities in order to reduce the delivered cost of logs. Mathematical models have been used to optimize the harvest scheduling at the operational level. However, in the existing literature, the number of machines assigned for each activity at each cut block was not considered as a decision variable. Also, the impact of the slope of cut blocks on the precedence relationship between harvesting activities was not considered in tprevious studies. In this work, a mathematical model is developed with the possibility of assigning multiple machines for the same harvest activity at each cut block, considering the precedence relationship between activities based on the slope of cut blocks in order to minimize the total cost of harvesting. This work is an extension of our previous work on detailed scheduling of harvesting. The model is applied to the harvesting operations of a large forest company in Coastal British Columbia, Canada. The model's result for operating cost is only 3.3% higher than the lowest possible operating cost. Only one machine has an idle time. For the same case study, the total cost of the developed model is about 34% lower than that of the previous model.

关键词： mixed-integer linear programming operational harvest scheduling precedence relationship harvesting costs machine assignment

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Coronavirus Optimization Algorithms for Minimizing Earliness, Tardiness, and Anticipation of Due Dates in Permutation Flow Shop Scheduling

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2023年第11期48卷 15713-15745页

作者： Fuchigami, Helio Yochihiro Prata, Bruno de Athayde Fed Univ Sao Carlos UFSCar Dept Prod Engn Rod Washington LuizKm 235 Sao Carlos SP Brazil Fed Univ Ceara UFC Dept Ind Engn Campus PiciBloco 735 Fortaleza CE Brazil

This study addresses a permutation flow shop scheduling problem to minimize a linear combination of earliness, tardiness, and assigned due dates. The production environment under study has several real-world applications, such as manufacturing, industrial maintenance, integrated production-distribution systems, potential disruptive environments, and other scenarios in which the due date is defined during sales negotiations with the customer. Four mixed-integer linear programming formulations were proposed and computationally evaluated, and their results were employed to measure the solution quality of the metaheuristics. Due to the complexity of the tackled problem, four coronavirus optimization algorithms based on recent optimization literature were implemented to solve it. A statistical analysis based on ANOVA (analysis of variance) and Tukey tests was performed to evaluate if the difference between the metaheuristics is statistically significant. The computational results demonstrated the superiority of the proposed metaheuristic Covid, especially in large-sized instances, outperforming an algorithm based on an iterated greedy algorithm (IGA) that we implemented for this problem.

关键词： Just-in-time scheduling Assignment due dates mixed-integer linear programming Bioinspired metaheuristics Coronavirus optimization

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Air-rail timetable synchronisation: Improving passenger connections in Europe within and across transportation modes

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2024年 115卷

作者： Buire, Clara Marzuoli, Aude Delahaye, Daniel Mongeau, Marcel Univ Toulouse ENAC Toulouse France Georgia Inst Technol North Ave NW Atlanta GA USA

This study addresses the integration of the railway and airline scheduling problems, in order to offer passengers smooth transfers between rail and air. This paper focuses on optimising the air and rail timetables at 18 major European airports including three hubs and their associated train stations. A multimodal passenger demand simulation, using constraint programming and based on real data, is proposed. A typical week, from Monday to Saturday, of December 2019 is analysed. Ten passenger demand simulations are run for each day, resulting in 60 test instances that are publicly released. The air-rail timetable synchronisation is applied to these 60 instances. Three scenarios are tested in which each operator agrees to change its schedule or not. Results show that changing the schedule of only 13% of European flights by 11 min, and half of trains scheduled to stop at the three hubs of 17 min, on average, could increase the number of suitable connections for passengers by 60%. In addition, if both airlines and railway operators adapt their schedules, passenger comfort is improved and operator costs are reduced, even more so than with unilateral changes.

关键词： Air-rail integrated timetable Optimisation Passengers Multimodal demand mixed-integer linear programming Constraint programming

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