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24th EEEIC International Conference on Environment and Electrical Engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： Yao, Leehter Ku, Cheng-Yu Teo, J.C. National Taipei University of Technology Department of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9798350355185

This paper proposes an aggregated energy management of multiple factories that purchased green energy collectively. These factories purchase green energy collectively to get a better price. The green energy is procured for each time step throughout the consumption day in a day ahead manner. On the consumption day, the green energy provider feeds green energy into the power grid at each time step, following the quantities that were purchased for those specific time intervals. The aggregated energy management system optimally dispatches the electrical power of the factories in an aggregated manner based on the purchased green energy profiles to maximize the consumption of the purchased green energy. A mixed integer linear programming (MILP) formulation is developed to carry out the aggregated energy management. To overcome the high computation time associated with conventional MILP, a linear programming relaxation technique is employed. This technique relaxes the binary variables, allowing them to take any value between 0 and 1, which enables the optimization problem to be solved in a very short time. After solving the optimization problem, the values of the variables are corrected back to binary values using a delicate method to ensure the feasibility of the solution. © 2024 IEEE.

关键词： mixed-integer linear programming

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A Hybrid Discrete Jaya Algorithm Based on Gene Expression programming for Heterogeneous Multi-Satellites Cooperative Observation 2

A Hybrid Discrete Jaya Algorithm Based on Gene Expression Pr...

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2nd International Conference on Artificial Intelligence and Automation Control, AIAC 2024

作者： Yang, Junxiang He, Lei College of Systems Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9798331529147

In disaster observation, disasters with different characteristics have different degrees of demand for the selection of observation satellites, which directly affects the imaging quality, specifically involving the matching problem between mission types and satellite types. In this paper, for this Heterogeneous multi-Agile Earth Observation Satellites Scheduling Problem (HAEOSSP), a mixed integer linear programming model is established, and the time-dependent transition time and task matching are taken into account. To solve HAEOSSP, a Hybrid Discrete Jaya algorithm based on Gene Expression programming (HD-Jaya-GEP) method is designed to evolve task assignment rule. Coded with GEP, the Jaya algorithm is discretized by a neighborhood-based strategy, while the single-satellite task scheduling is solved by a mature meta-heuristic algorithm. Finally, simulation experiments are performed to evaluate the generalization of HD-Jaya-GEP, which validates the effectiveness and capability. © 2024 IEEE.

关键词： mixed-integer linear programming

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Algorithm for the robust shortest path problem with multimodal transportation 8

Algorithm for the robust shortest path problem with multimod...

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8th International Conference on Traffic Engineering and Transportation System, ICTETS 2024

作者： Guo, Jinzuo Liu, Tianyu Song, Guopeng Guo, Bo College of Systems Engineering National University of Defense Technology Changsha410073 China

ISBN: (数字)9781510686298

ISBN: (纸本)9781510686281

This paper explores the challenges of finding robust shortest paths in multimodal transportation networks. This study develops a robust mixed-integer programming model, taking into account practical constraints related to parameter uncertainty in transportation times. We propose a modified Dijkstra algorithm that integrates parameter uncertainty with multimodal transportation. The findings indicate that the proposed approach is capable of producing optimal solutions for the robust shortest path problem involving multimodal transportation in the context of time uncertainty, highlighting its practical relevance. © 2024 SPIE.

关键词： mixed-integer linear programming

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Improved Bounds of integer Solution Counts via Volume and Extending to mixed-integer linear Constraints 30

Improved Bounds of Integer Solution Counts via Volume and Ex...

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30th International Conference on Principles and Practice of Constraint programming, CP 2024

作者： Ge, Cunjing Biere, Armin National Key Laboratory for Novel Software Technology Nanjing University China School of Artificial Intelligence Nanjing University China University of Freiburg Germany

ISBN: (纸本)9783959773362

Solution counting and solution space integration over linear constraints are important problems with many applications. Previous works addressed either only counting integer points in polytopes (integer counting) with integer variables or alternatively only computing the volume of polytopes (solution space integration) on variables over the reals, including approximating the integer count via a polytope's volume. We are not aware of a non-trivial algorithm which addresses the mixed case, where linear constraints are over mixed integer and real variables. In this paper, we propose a new randomized algorithm to approximate guarantees (bounds) of integer solution counts. Then we present upper and lower bounds for solution space integration over mixed-integer linear constraints. Thus, proposed algorithms can be extended to mixed-integer cases as well. The experiments show that approximations are often very close to exact results in practice, and bounds approximated by our algorithm are often tight and useful. © Cunjing Ge and Armin Biere.

关键词： mixed-integer linear programming

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Optimal Decision Tree Design for Near Real-Time Control of Battery Energy Storage Systems 26

Optimal Decision Tree Design for Near Real-Time Control of B...

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26th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2024

作者： Handel, Katrin Anitha, Angellina Ebenezer Rigo-Mariani, Remy Schulte, Katrin Haubrock, Jens University of Applied Sciences and Arts Bielefeld Institute for Technical Energy Systems Bielefeld Germany University Grenoble Alpes CNRS Grenoble INP G2Elab Grenoble France

ISBN: (纸本)9798331532833

The increasing numbers of distributed energy resources (DER) incur new challenges for the energy supply due to the volatilities and uncertainties of renewable energies. To utilize the benefits of DER, a combination with storage systems and intelligent controls is necessary. Commonly used control methods are based on Model Predictive Control (MPC) with forecast and optimization, which require computational capabilities at the DER on a level, on which the distribution system operator (DSO) has no access. This paper proposes a control algorithm based on data, which combines a model-based and an artificial intelligence (AI) based approach to utilize benefits from both methods while compensating for their drawbacks. mixed-integer Quadratic programming (MIQP) is used to generate training and testing data for a decision tree (DT). The investigation of the optimal composition of the training data and the optimal architecture of the DT are the main focus of this paper. © 2024 IEEE.

关键词： mixed-integer linear programming

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Optimised architecture design for an MEA power distribution system considering load profile and fault-tolerance

Optimised architecture design for an MEA power distribution ...

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IEEE International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles / International Transportation Electrification Conference (ESARS-ITEC)

作者： Wang, Xin Atkin, Jason Yeoh, Seang Bozhko, Serhiy Univ Nottingham Dept Elect & Elect Engn Fac Engn Nottingham England Univ Nottingham Computat Optimisat & Learning Lab Sch Comp Sci Nottingham England

ISBN: (纸本)9798350346893

With the development of More Electric Aircraft (MEA), novel power distribution systems (PDSs) are required to meet significantly increased electrical load demands onboard. Nevertheless, newer designs must comply with the strict flight operational and safety requirements, while achieving optimisation aims, such as reducing aircraft weight and energy consumption. This paper proposes a two-stage optimisation design method for a novel PDS investigated for MEA. Two optimal power scheduling-based models for minimising power losses and PDS weight are formulated in mixed-integer linear programming (MILP). The first model considers varying load demands and is solved for all flight stages simultaneously in the first design stage for weight minimisation. The obtained architecture is further optimised for all faulty scenarios and selected typical fight stages simultaneously in the second design stage to improve the PDS reliability. Consequently, a low power loss, light weighted, and fault-tolerant PDS architecture is obtained. A case study is provided to exemplify the improvement in the PDS by adopting the proposed method.

关键词： More electric aircraft power distribution system architecture design two-stage optimisation mixed-integer linear programming

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Scalable and Near-Optimal ε-Tube Clusterwise Regression 20th

Scalable and Near-Optimal ε-Tube Clusterwise Regression

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20th International Conference on the Integration of Constraint programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Chembu, Aravinth Sanner, Scott Khalil, Elias B. Univ Toronto Dept Mech & Ind Engn Toronto ON Canada

ISBN: (纸本)9783031332708;9783031332715

Clusterwise Regression (CLR) methods that jointly optimize clustering and regression tasks are useful for partitioning data into disjoint subsets with distinct regression trends. Due to the inherent difficulty in simultaneously optimizing clustering and regression objectives, it is not surprising that existing optimal CLR approaches do not scale beyond 100 s of data points. In an effort to provide more scalable and optimal CLR methods, we propose a novel formulation of the problem that takes inspiration from e-tubes in Support Vector Regression (SVR). The advantage of this novel formulation, which aims to assign data points to clusters in order to minimize the largest e-tube that encapsulates the regressed data, is that it admits an optimal MILP formulation. Furthermore, given that each constraint in our formulation corresponds to a single data point, we propose an efficient row generation solution that can optimally converge for the full dataset while only requiring optimization over a subset of the data. Our results on a variety of synthetic and benchmark real datasets show that our Clusterwise Regression MILP formulation provides near-optimal solutions up to 100,000 data points and the smallest data-encapsulating e-tubes among CLR alternatives.

关键词： Clusterwise Regression Row Generation mixed-integer linear programming

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Sustainable Short-Term Production Planning Optimization

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SN Computer Science 2023年第6期4卷 824页

作者： Zanella, Fernando Vaz, Clara Bento Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança (IPB) Campus de Santa Apolónia Bragança 5300-253 Portugal Laboratório para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança (IPB) Campus de Santa Apolónia Bragança 5300-253 Portugal Centre for Management and Industrial Engineering (CEGI/INESC TEC) Porto Portugal

This study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a mixed-integer linear programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost;(2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon. © 2023, The Author(s).

关键词： mixed-integer linear programming Responsible production Short-term production planning

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A FACILITY LOCATION MODEL FOR UNCREWED SURFACE VESSELS IN THE MARITIME SURVEY INDUSTRY 42

A FACILITY LOCATION MODEL FOR UNCREWED SURFACE VESSELS IN TH...

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ASME 42nd International Conference on Ocean, Offshore and Arctic Engineering (OMAE)

作者： Moorlag, Lucas Jiang, Xiaoli Delft Univ Technol Delft Netherlands

ISBN: (纸本)9780791886922

The maritime industry is preparing for a future where human presence is no longer required on board of ships. This will revolutionize maritime operations and consequentially introduce unprecedented challenges to the corresponding logistics. This paper provides a first piece of reflection on mixed-integer linear programming (MILP) problems regarding remote and autonomous operations in the maritime industry. A non-standard facility location problem (FLP) is constructed to determine the optimal locations for a number of facilities serving as refueling stations, and to obtain the optimal heterogeneous vessel fleet size & mix to satisfy the inspection demand of North-Sea assets over a multi-period timeframe. The model combines distinctive vessel routing behavior to assess a heterogeneous fleet of both remotely operated vessels and traditional vessels in the maritime survey industry. The simulation results are reported for a real case study commissioned by geo-data company Fugro. The final results of the model suggest that the effective establishment of facility locations and corresponding fleet allocation can reduce the operational costs and environmental footprint of the survey operations in the North-Sea.

关键词： Facility location problem mixed-integer linear programming centroid-based routing uncrewed surface vessels robodocks maritime survey industry

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Formulations for the Split Delivery Capacitated Profitable Tour Problem 23rd

Formulations for the Split Delivery Capacitated Profitable T...

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23rd International Conference on Computational Science and its Applications (ICCSA)

作者： Caspar, Marvin Schermer, Daniel Wendt, Oliver Univ Kaiserslautern Landau Business Informat Syst & Operat Res BISOR Postfach 3049 D-67653 Kaiserslautern Germany

ISBN: (纸本)9783031368042;9783031368059

In this paper, we study the Split Delivery Capacitated Profitable Tour Problem (SDCPTP) that extends the profitable tour problem by a fleet of vehicles and the possibility of split deliveries. In the SDCPTP, the objective is to select a subset of requests and find for each vehicle a feasible tour such that the prize collected by fulfilling the selected requests net of the cost of delivery is maximized. We propose three mixed-integer linear programming formulations for modeling the SDCPTP. These formulations differ primarily in their treatment of the subtour elimination constraints within the branch-and-cut algorithm. The first of these formulations is applicable to the more general asymmetric case, whereas the other two are computationally more efficient in presence of symmetric variants of the problem. Using benchmark instances from the literature, we provide a detailed numerical study that demonstrates the effectiveness of a state-of-the-art solver in tackling these models. For managerial insights, we perform a sensitivity analysis on the SDCPTP with respect to the number of vehicles and requests as well as the benefits of enabling split delivery.

关键词： mixed-integer linear programming Branch-and-Cut Algorithm Capacitated Profitable Tour Problem Split Delivery

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