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检索条件"主题词=Mixed integer linear programming"

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An initial framework for the less-than-truckload problem: order allocation and planning

An initial framework for the less-than-truckload problem: or...

引用

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

作者： Onur Ozturk Najat Bara Faculty of Telfer School of Management University of Ottawa Ottawa Canada Department of Industrial Engineering CentraleSupelec Gif-sur-Yvette Cedex France

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

In the less-than-truckload problem, the transportation cost for each client is a piece-wise linear function as the incurred unit transportation decreases with the occupied volume in the truck. In this paper, we consider the order consolidation when different products are purchased from the same suppliers. Production orders can have different volumes and delivery due dates. We aim to minimize the total purchasing cost and the transportation cost in the presence of multiple suppliers located in different locations. We provide a mixed integer linear programming formulation that can solve moderate size instances.

关键词： Costs Metaheuristics Transportation Production Mathematical models mixed integer linear programming Planning Numerical models Resource management Capacity planning

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Optimizing Industrial Energy Systems: A Multi-Objective Approach to Decarbonization and Cost Efficiency

Optimizing Industrial Energy Systems: A Multi-Objective Appr...

引用

Smart Power & Internet Energy Systems (SPIES), International Conference on

作者： Simon Kammerer Constantin Chaumet Christian Rehtanz Jakob Rehof Institute of Energy Systems Energy Efficiency and Energy Economics TU Dortmund University Dortmund Germany Department of Computer Science Software Engineering by Algorithms and Logic TU Dortmund University Dortmund Germany Lamarr Institute for Machine Learning and Artificial Intelligence TU Dortmund University Dortmund Germany

ISBN: (数字)9798350368864

ISBN: (纸本)9798350368871

The transition to a renewable energy (RE) based future necessitates transformative changes in the industrial sector's energy infrastructure. As industries strive to maintain economic viability while achieving decarbonization goals, there is a pressing need for innovative strategies that integrate renewable energy sources, enhance energy efficiency, and optimize energy procurement. This paper presents a comprehensive approach that leverages a combination of simulation and optimization methods to address the challenges of designing and operating complex future industrial energy systems. A nested optimization approach is proposed, which combines mixed-integer linear programming (MILP) for operational optimization with black-box optimization techniques. The approach enables exploration of solutions for optimal infrastructure investment as well as operational strategies, allowing companies to benchmark a wide range of infrastructure and contractual options. This provides these companies with the means to determine long-term, cost-effective pathways that minimize CO2 emissions, avoid malinvestments, and ensure the sustainable operation of energy systems. A case study involving a German waste processing company illustrates the practical application of our approach, highlighting how strategic decisions in asset dimensioning, energy flexibility utilization, and renewable integration can significantly impact both costs and emissions.

关键词： Procurement Renewable energy sources Costs Closed box Optimization methods Companies Pressing Low carbon economy mixed integer linear programming Investment

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Energy-Aware Coverage Path Planner for Multirotor UAVS

Energy-Aware Coverage Path Planner for Multirotor UAVS

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Luis Escobar Guilherme A. S. Pereira Department of Mechanical and Aerospace Engineering of the Benjamin M. Statler College of Engineering and Mineral Resources at West Virginia University Morgantown WV USA

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Coverage Path Planning (CPP) is crucial for UAV applications such as inspection and surveying. While existing CPP methods often focus on minimizing distance or time, energy consumption remains a critical, relatively unexamined constraint, especially for multirotor drones. This paper proposes a novel CPP approach that directly incorporates an energy model into the path-planning process. By utilizing a mixed integer linear programming (MILP) framework and an energy model, the proposed method aims to minimize energy consumption while ensuring complete coverage of the target area. Simulations and experimental results demonstrate that the proposed approach gives optimal solutions, and using this richer cost function reduces the processing time for the MILP problem, opening the door for faster online CPP planners.

关键词： Energy consumption Atmospheric modeling Inspection Autonomous aerial vehicles Cost function Path planning mixed integer linear programming Aircraft Drones

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Prosumer Centric Strategy for Utilization of EV in Microgrid

Prosumer Centric Strategy for Utilization of EV in Microgrid

引用

Sustainable Energy and Future Electric Transportation (SEFET), International Conference on

作者： Sri Lakshmi. E S. P. Singh Department of Electrical and Electronics Engineering Bharat Institute of Engineering and Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology IIT(BHU) Varanasi Varanasi India

ISBN: (数字)9798350383997

ISBN: (纸本)9798350384000

The paper explores the optimization of microgrid operation with solar energy, energy Storage System, and electric vehicles as additional support to the grid. It introduces bidirectional power flow strategies to utilize Electric vehicle (EV) energy for both home and grid power, regulated by managing the rate of charge/discharge. The proposed strategy considers EV availability, transformer loading, and day-ahead prices. Using Markov model with factual hourly vehicle usage data, the paper predicts EV availability. Its primary objective is to minimize the operational costs for prosumers while minimizing battery degradation. The paper formulates schedule and battery degradation of EV/ESS as a mixed-integer problem, solved using mixed integer linear programming (MILP) with IBM CPLEX optimizer. Furthermore, the paper also introduces incentive pricing strategy to boost EV participation in energy transactions and reduce grid dependency.

关键词： Degradation Schedules Uncertainty Transportation Microgrids Electric vehicles Transformers Batteries mixed integer linear programming Optimization

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Economic Operation for Prosumers and Shared Energy Storage Based on Stackelberg Game

Economic Operation for Prosumers and Shared Energy Storage B...

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Electrical Engineering and Control Technologies (CEECT), Conference on

作者： Duanchao Li Wen Tang Wei Wang Li Zhang Feixiang Peng Jun Tao Xincun Shen Manman Ren State Grid Anhui Electric Power Co. Ltd Hefei China Anhui University Hefei China State Grid Anhui Electric Power Co. Ltd Electric Power Science Research Institute of State Grid Anhui Electric Power Co. Ltd Hefei China

ISBN: (数字)9798331528096

ISBN: (纸本)9798331528102

With the increasing proportion of renewable energy, shared energy storage(SES) is going to be a significant part in power system. It can alleviate the impact of clean energy generation access to the grid. Aiming at the economic operation optimization problem of SES as an independent individual participating in the power market, a new business model of SES is studied, and an optimization operation strategy for prosumers and SES based on Stackelberg game is established. Among them, the upper-level model is responsible for solving the maximum daily operation value of SES, and the lower-level models are responsible for solving the minimum daily operation cost of prosumers. According to the Karush-Kuhn-Tucher (KKT) condition, the lower-level models are converted into the constraints of the upper-level one, and the Big-M method is used to linearize the nonlinear constraints. A pricing mechanism based on the supply-demand ratio is used by the SES, and the new trading prices between $\operatorname{SES}$ and prosumers are calculated according to the optimization results of the Stackelberg game. The optimal solution of the model can be obtained through continuous iteration. The rationality and effectiveness of constructed model in this paper can be verified by example analysis. It is proved that the proposed SES business model can help energy storage(ES) power stations establish an independent entity in the new power system.

关键词： Optimization models Games Pricing Power markets Power systems mixed integer linear programming Optimization Power generation Business Energy storage

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Modeling and Optimizing Aircraft-Cargo Compatibility and Risk Exposure Challenges in 1-M/M-1 Transportation Network

Modeling and Optimizing Aircraft-Cargo Compatibility and Ris...

引用

IEEE International Conference on Industrial Engineering and Engineering Management

作者： Deepak Kumar Kushwaha Goutam Sen Department of Industrial & Systems Engineering Indian Institute of Technology Kharagpur West Bengal India

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

In emergencies, the efficiency of logistics planning and transportation operations is critical for the timely delivery of essential supplies. This study addresses the challenges of aircraft and cargo incompatibility while minimizing the risk associated with routes to optimize air cargo transportation. An innovative optimization framework is proposed to align cargo attributes with aircraft specifications and capabilities while considering route-specific risks. The research highlights the significance of ensuring load (cargo)-compatibility and optimal space utilization within a one-to-many-to-one (1-M/M-1) transportation network. The proposed model is particularly relevant for strategically transporting sensitive cargo, equipment, and supplies during military crises and humanitarian missions. By employing the Branch and Cut (B&C) algorithm, the study evaluates the performance of the mixed-integer linear programming (MILP) model in solving complex, real-world problems. Illustrative examples demonstrate the model’s application, emphasizing the crucial aspects of emergency transportation and the need for an integrated approach to enhance the safety and efficiency of air logistics operations.

关键词： Atmospheric modeling Transportation Military aircraft Real-time systems Planning mixed integer linear programming Aircraft Optimization Logistics Load modeling

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Techno-Economic Optimization of Services Stacking for a Battery Participating to Electricity Spot Markets

Techno-Economic Optimization of Services Stacking for a Batt...

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International Conference on European Electricity Market, EEM

作者： Andrea Scrocca Filippo Bovera Giuliano Rancilio Maurizio Delfanti Matteo Zatti Department of Energy Politecnico di Milano Milan Italy LEAP s.c.a.r.l. Laboratorio Energia Ambiente Piacenza Piacenza Italy

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

This study explores the optimization of services stacking for a battery providing primary, secondary, and tertiary frequency regulation while participating in the day-ahead market in Italy. Formulated as a two-stage stochastic mixed integer linear programming (MILP) problem, the objective is to maximize daily revenues accounting for uncertainty related to tertiary reserve offers acceptance. The paper investigates how technical and financial market design parameters impact battery's revenues and optimal strategy. Key findings indicate that the highest economic gains are associated with batteries having intermediate Energy-to-Power Ratio (EPR): too high EPR increase the investment risk, and very low EPR are optimal only under specific market conditions. The study highlights the need for proper balancing capacity payments to incentivize batteries participation to flexibility markets. The market value of diverse services also drives investments choices in terms of batteries’ design, specifically influencing the EPR value.

关键词： Economics Uncertainty Electricity Stacking Europe Batteries mixed integer linear programming

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Optimization Technique for Electric Bus Fleet Schedules with a-Priori Trip Disaggregation

Optimization Technique for Electric Bus Fleet Schedules with...

引用

International Conference on Intelligent Transportation

作者： I Kadek Jimmy Sardana Benjamin Blat Belmonte Paul Heckelmann Stephan Rinderknecht Department of Informatics Technical University of Darmstadt Germany Department of Mechanical Engineering Technical University of Darmstadt Germany

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Electric vehicles represent a great opportunity to electrify the public transportation sector, and thereby mitigate greenhouse gas emissions and noise pollution among others. Due to the limited range of electric buses compared to their internal combustion engine counterparts, the scheduling process has to be rethought. A fleet operator has to decide between different charging strategies such as depot-charging, opportunity-charging, or a combination of both. The existence of different vehicle types, e. g., regarding battery capacity and passenger capacity, further complicates the matter. We introduce a multiple vehicle type scheduling problem with partial charging (MVTSP-PC) that can optimize existing fleet schedules. Our approach is based on the disaggregation of the existing bus schedule. Then, with an exact solution approach using mixed-integer linear programming and route restriction strategies we identify optimal schedules while considering computational resources. With the presented approach bus schedules for whole weeks can be efficiently re-adapted. The approach designs the optimal schedule on a daily basis, and subsequently uses a heuristic approach for the vehicle-to-route assignment when concatenating the days.

关键词： Schedules Pollution Processor scheduling Urban areas Noise Internal combustion engines Optimal scheduling Electric vehicles mixed integer linear programming Public transportation

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Fronthaul Resource Optimization for Cell-Free Massive MIMO Networks

Fronthaul Resource Optimization for Cell-Free Massive MIMO N...

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International Workshop on Reliable Networks Design and Modeling (RNDM)

作者： Ameya G. Joshi Nguyen Tuan Khai Thomas Bauschert Technische Universität Chemnitz Chemnitz Germany

ISBN: (数字)9798331518189

ISBN: (纸本)9798331518196

Cell-free massive multiple-input multiple-output (mMIMO) is expected to be a key technology in 6G and beyond networks where User Equipments (UEs) are jointly served by multiple Radio Units (RUs) in order to enhance the throughput and reliability. This joint cooperation leads to a significant increase in fronthaul (FH) resource requirements as UE traffic has to be routed simultaneously between multiple RUs (constituting the so-called RU cluster for a UE) and a cluster processor (CP) located at a Distributed Unit (DU) site. In this paper we propose a novel two-step algorithm for FH network resource optimization with the objective to balance the traffic load on the FH links and the processing load at the DU sites. In the first step, we determine the cluster specific traffic for a given UE/traffic density distribution within the coverage area and a given cluster formation scheme using a Monte Carlo approach. For the second step, we formulate a mixed integer linear programming (MILP) optimization problem to balance the FH link loads and the processing loads at the DU sites - i.e. we solve the FH traffic routing and CP placement problem. Finally we apply our method on a cell-free O-RAN example scenario and investigate the impact of different configuration parameters on the optimization results. Our approach provides a generalised way to optimize FH resources in user-centric cell-free massive MIMO network deployments.

关键词： Monte Carlo methods Massive MIMO Telecommunication traffic Open RAN Throughput Routing mixed integer linear programming Reliability Optimization MIMO communication

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Data-Driven Economic analysis of hydrogen-power coupled integrated energy system

Data-Driven Economic analysis of hydrogen-power coupled inte...

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Data Science and Information Technology (DSIT), International Conference on

作者： Zhang Yan Yuan Zi Zhu Zhentao Jin Zhenqiang Wang Mulan Xu Hao Wang Hairong Tan Wenyi School of Economics and Management Nanjing Institute of Technology Nanjing China School of Electric Power Engineering Nanjing Institute of Technology Nanjing China Ministry of Industry and Technology Jiangsu Power Transmisson & Transformation Co.Ltd Nanjing China School of Management Engineering Nanjing Institute of Technology Nanjing China School of Environmental Engineering Nanjing Institute of Technology Nanjing China

ISBN: (数字)9798350384093

ISBN: (纸本)9798350384109

Energy system choices for zero-carbon parks are challenged by the drive towards a low-carbon transition. Traditional wind-power-gas integrated energy systems centred on natural gas and combined heat and power (CHP) are limited by high carbon capture and storage costs. The aim of this study is to assess the economic viability of an innovative hydrogen-electricity coupled integrated energy system centred on hydrogen production from renewable energy sources and to conduct a comparative analysis with conventional systems. The study begins with the collection of historical data on wind speed and solar radiation in the park over a number of years, which is used to analyse the output characteristics of the wind and photovoltaic systems in depth, providing a solid data base for the optimal design of the hydrogen-electric coupled system. Next, a techno-economic model was constructed to meet the park's demand for electricity, heat and transport energy. The capacity of each component in both systems was optimally configured to reduce the annualised cost of the system through a mixed integer linear programming (MILP) approach. Based on this, a comprehensive techno-economic analysis was conducted to compare the economic indicators of the two systems. The results of the analyses show that the hydrogen-electric coupling system has significant economic advantages, including a higher net present value (improved by 70.79%), a shorter payback period (reduced by 6.61%), and a higher internal rate of return. Sensitivity analyses further revealed the main factors affecting the economics of the hydrogen-electric coupling system, including the demand for hydrogen from vehicles in the park, electrolyser costs and wind turbine costs. The findings of this study provide an important reference for planning and decision-making on the energy system of a zero-carbon park and highlight the potential of hydrogen in the future energy supply of the park.

关键词： Economics Couplings Renewable energy sources Costs Hydrogen Data science Wind turbines mixed integer linear programming Solar radiation Wind forecasting

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