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Demand Modeling and Operations Optimization for Advanced Regional Air Mobility

Demand Modeling and Operations Optimization for Advanced Reg...

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AIAA Aviation Forum and Exposition

作者： Justin, Cedric Y. Payan, Alexia P. Mavris, Dimitri N. Georgia Inst Technol Aerosp Syst Design Lab Atlanta GA 30332 USA Georgia Inst Technol Adv Aerosp Anal Atlanta GA 30332 USA

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

Commuter operations refer to the transportation of passengers on small capacity aircraft over short distances. These services have historically been plagued by high operating costs, yielding marginally profitable operations. The recent convergence of new technologies in autonomy and electric propulsion brings a step change in aircraft operating efficiency which may significantly improve the economics and environmental footprint of these vehicles. The next challenge is to optimize operations to match the demand and best utilize these assets. To do so, forecasting the demand for these new services is critical. First, we develop a demand model based on an empirically-calibrated generalized cost of travel combined with a multinomial logit model. Next, we investigate the design of sustainable and profitable regional air mobility operations by optimizing the network, schedule, and assignment of aircraft to flights. We develop a novel half-leg half-itinerary mixed-integer linear program to solve the integrated flight scheduling and fleet assignment problem using a multi-objective hierarchical optimization balancing the maximization of operating profits and the minimization of operating emissions. This helps identify promising regional air mobility markets, assess their economical viability, and select an optimum fleet composition to best serve these markets. The proposed framework is implemented in the United States Northeast Corridor using a fleet of three small-gauge electrified aircraft ranging in size from 9 passengers to 48 passengers. Several what-if scenarios are investigated with respect to the battery technology, the relative importance of profit and carbon emission objectives, and the network topology to identify their impact on the operations in terms of number of profitable routes, number of airports served, number of passengers carried, operating profits and operating emissions. Results highlight a significant potential for profitable regional air mobility ser

关键词： Air Mobility Operating Costs mixed integer linear programming Discrete Choice Models Electric Propulsion Department of Transportation Retractable Landing Gear Energy Density Cost Per Available Seat Mile Electricity

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A MILP Model for Reusable Containers Management in Automotive Plastic Components Supply Chain 22nd

A MILP Model for Reusable Containers Management in Automotiv...

引用

22nd IFIP WG 5.5 Working Conference on Virtual Enterprises (PRO-VE)

作者： Guzman, Eduardo Andres, Beatriz Poler, Raul Univ Politecn Valencia UPV Res Ctr Prod Management & Engn CIGIP Alicante 03801 Spain

ISBN: (纸本)9783030859695

The automotive sector operates under the just-in-time (JIT) approach, but variations in demand mean that first-tier suppliers generate an accumulation of stocks at second-tier suppliers. Second-tier suppliers have a limitation of storage space, reason to limit their production to the size of the warehouse, but always attending the first-tier demand plan. Afurther limitation of the second-tier supplier is the number of empty reusable containers that the first-tier supplier delivers to the second-tier supplier and that are used to package the injected plastic components. The reusable filled containers are returned to the first-tier supplier, according to the plastic components demand plan. Thus, a closed-loop logistic is carried out between first and second-tier suppliers. This study proposes, from the second-tier perspective, a mixed integer linear programming (MILP) model for fleet sizing decisions of the cardboard containers in a production system. The model determines the number of cardboard containers that second-tier supplier has to use when the production is higher than the number of available reusable containers.

关键词： Lot-sizing Scheduling Supply chain mixed integer linear programming Closed-loop supply chain Sustainability

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Scheduling Drillships in Offshore Activities 12th

Scheduling Drillships in Offshore Activities

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12th International Conference on Computational Logistics (ICCL)

作者： Azzariti Brasil, Rafael Gardel de Mesquita, Marco Aurelio Miyake, Dario Ikuo Montanher, Tiago Ronconi, Debora P. Univ Sao Paulo Dept Prod Engn Av Luciano Gualberto 1380Cidade Univ BR-05508010 Sao Paulo SP Brazil Univ Vienna Fac Math Oskar Morgenstern Pl 1 A-1090 Vienna Austria

ISBN: (纸本)9783030876722;9783030876715

This paper addresses the scheduling of offshore oil well construction using drilling vessels. Drilling costs constitute a substantial part of the total development costs for an offshore field, thus planning the efficient use of drilling rigs is crucial to ensure economic feasibility of oil and gas exploration and production (E&P) projects. The objective of this study is to minimize the completion time of all operations involved in the development of subsea wells considering the availability of the drilling rigs. These activities are drilling and completion of the well, and maintenance activities. Technical constraints and availability of the drilling vessels and release dates and precedence constraints of the activities are considered. In addition, vessel eligibility restrictions are respected. A mixed integer linear programming model was developed considering the goals and constraints above. Numerical experiments using instances based on real-world situations show adequate behavior, which demonstrates that it faithfully represents the situation portrayed and can be used, combined with more advanced optimization techniques, to achieve better results.

关键词： Oil wells Offshore activities mixed integer linear programming

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Multi-Objective Design Optimization of Multicopter using Genetic Algorithm 18

Multi-Objective Design Optimization of Multicopter using Gen...

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18th International Bhurban Conference on Applied Sciences and Technologies (IBCAST)

作者： Ayaz, Ahsan Rasheed, Ashhad Inst Space Technol IST Dept Aeronaut & Astronaut Islamabad Pakistan

ISBN: (纸本)9781665405164

Different research groups work together with different objectives in a single project. In Multicopter, Power Electronics has been assigned a task to maximize flight time whereas structural and inertial group requires light weight structure with minimum power consumption respectively. Selecting optimal readily available off the shelf components as per the mission requirement can be tricky job. It requires a trade-off between objective functions. There is significant amount of work done on multirotor using single objective optimization depending upon mission requirement but limited data is available for multiple objective optimization. One major drawback of integrating off-the-shelf components in optimization is that while optimizing one objective, the other objective may be blown out of proportions because of the same variable dependence. A multi-objective design optimization provides a pareto front which can really help the designer decide which variables to choose according to mission requirement. The pareto front actually demonstrates the trade-off between the objectives. The research aims to highlight the usability of genetic algorithm in multi-objective design optimization of multirotor with off-the-shelf components. Flight Time, power consumption and price are optimized simultaneously without payload. mixed integer linear programming incorporates indexed or boolean variable. However the adaption of indexed variable into Genetic Algorithm is not completely straight forward and is therefore discussed in the paper. The variables are indexed as per the selection of parameters. These parameters are actuator (combination of propeller and motor), high efficiency DC battery and Airframe. The resultant score diversity, fitness function and Pareto fronts indicated fairly convergent and promising results. However, larger set of components offering more trade-offs between various fitness functions would definitely challenge this setup.

关键词： Single Objective Optimization Multiple Objective Optimization mixed integer linear programming Genetic Algorithm Variables Knitting Score Diversity Fitness Function Pareto Fronts

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Real-time dispatching optimization of high-speed rail based on model predictive control under partial interruption

Real-time dispatching optimization of high-speed rail based ...

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IEEE Intelligent Transportation Systems Conference (ITSC)

作者： Luo, Meixuan Zheng, Wei Huang, Kang Beijing Jiaotong Univ Natl Res Ctr Railway Safety Assessment Beijing 100044 Peoples R China Beijing Jiaotong Univ Beijing Key Lab Intelligent Traff Data Secur & Pr Beijing 100044 Peoples R China China State Railway Grp Co Ltd Railway Safety Res Ctr Beijing 100044 Peoples R China

ISBN: (纸本)9781728191423

The high-speed railway network has a huge structure and interruption problems occur from time to time. The automatic and intelligent train operation adjustment is of great significance to assist dispatchers in decision-making. In this paper, the mixed integer linear programming (MILP) model was established in the case of the failure of one-way passing capacity in local network interval, and the model predictive control (MPC) algorithm was introduced into the study of railway interruption problem, so as to reduce the impact of interruption on train operation and effectively shorten the calculation time of this large-scale problem. Taking into account the uncertainty of the scene in the case of interruption, online optimization was realized through the feedback control algorithm. In addition, we studied the spread of the delay caused by a partial interruption of a line to adjacent lines. The intersection of Beijing-Shanghai high-speed rail and Tianjin-Qin high-speed rail was employed as a case to verify its effectiveness.

关键词： Uncertainty Predictive models Prediction algorithms Rail transportation Real-time systems mixed integer linear programming Feedback control

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ECADA: An Edge Computing Assisted Delay-Aware Anomaly Detection Scheme for ICS

ECADA: An Edge Computing Assisted Delay-Aware Anomaly Detect...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Chao Sang Jianhua Li Jun Wu Wu Yang School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Graduate School of Information Production and Systems Waseda University Japan College of Computer Science and Technology Harbin Engineering University China

ISBN: (数字)9798350358261

ISBN: (纸本)9798350358278

Today, with more and more devices in the industrial control system (ICS), the risk becomes higher and brings more attack surfaces. The need for reliable anomaly detection systems is increasing. Traditional SCADA-based detection systems deployed are difficult to assess large-scale control systems accurately, and novel AI-based technologies struggle to ensure timely response. In this paper, we propose an edge computing assisted delay-aware anomaly detection (ECADA) scheme for ICS, which considers both the accuracy and timeliness, and ensures that abnormal conditions can be accurately detected and handled in a short time. First, we model the components in ICS as three layers, taking network resources, delay, and reliability into consideration. Second, we convert the anomaly detection procedure into a decision making problem. By dividing the warning capabilities into various levels, the flexibility of the anomaly detection system is enhanced. Third, we cast a mixed-integer linear programming (MILP) problem to find the efficient anomaly detection mechanism, so that it can be dynamically scheduled to achieve the tradeoff between reliability and timeliness. We use an real-world industrial system dataset for experimental evaluation. By comparing with various traditional anomaly detection methods, it is proved that ECADA can always ensure reliable response of anomaly detection system in various network environments.

关键词： Computational modeling Industrial control Reliability engineering Sensors mixed integer linear programming Task analysis Low latency communication

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Power System Robust Operation Considering the Extreme Output of Renewable Power Generation

Power System Robust Operation Considering the Extreme Output...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Yue Chen Yinguo Yang Tianyuan Xu Zhiren Zhang Pingping Xie Shuangxi Wu Power Dispatching Control Center Guangdong Power Grid Co. Ltd Guangdong China State Key Laboratory on Electrical Insulation and Power Equipment Xi’an Jiaotong University Xi’an China

The topic of power system robust operation has been widely explored in recent years. However, the detailed reason why considering renewable energy extreme output is so important is seldom discussed. This paper employs a SCUC (Security Constrained Unit Commitment) model to study the influence of potential extreme output of renewable power generation on power system operation. The results are revealed through a series of case studies via the comparisons of load curtailment. The SCUC model is formulated as a MILP (mixed integer linear programming) problem and solved by customized C&CG (Column and Constrained Generation) algorithm which is implemented on a modified IEEE 24 node system.

关键词： Electrical engineering Renewable energy sources Asia Scheduling Power systems mixed integer linear programming Security

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Virtual-Coupling Operation for High-Speed Rail based on Following-Train Speed Profile Optimization 32

Virtual-Coupling Operation for High-Speed Rail based on Foll...

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32nd IEEE Intelligent Vehicles Symposium (IV)

作者： Xu, Bin Wu, Chaoxian Lu, Shaofeng Xue, Fei Xian Jiaotong Liverpool Univ Dept Elect & Elect Engn Suzhou Peoples R China Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA South China Univ Technol China Shien Ming Wu Sch Intelligent Engn Guangzhou Guangdong Peoples R China Univ Liverpool Dept Elect Engn & Elect Liverpool Merseyside England

ISBN: (纸本)9781728153940

With the increasing railway transportation demands, railway operators need to enhance the capacity in high traffic corridors to improve transportation efficiency. The establishment of the concept "virtual coupling (VC)" provides an effective method for achieving higher capacity. The core idea is to reduce the train separation and to enable a maximized number of trains on the track. Based on the emerging modern communication techniques, the synchronous operation between different trains to form the coupled state can be achieved without any physical connection. In this paper, a following-train speed profile optimization model is proposed by employing mixed integer linear programming (MILP) approach to achieving VC with the leading train. Therefore, the safety constraints (i.e. moving block signaling (MBS)) are considered as the most important physical border between each train under the VC operation. Three cases under different scenarios are conducted on a generic high-speed rail, which proves the effectiveness of the proposed method on the speed profile optimization for following trains under the VC operation. It also shows the factors influencing the time headway under minimized-separation operations.

关键词： Couplings Intelligent vehicles Transportation Block signalling Rail transportation Safety mixed integer linear programming

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Vehicle Routing Problem with Pickup, Relay, and Delivery: Delivery Task Assignment in Hybrid-Transit Logistics Network

Vehicle Routing Problem with Pickup, Relay, and Delivery: De...

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AIAA Aviation Forum and Exposition

作者： Damanik, Joshua Julian Choi, Han-Lim Korea Adv Inst Sci & Technol Aerosp Engn Dept Daejeon South Korea

ISBN: (数字)9781624106101

ISBN: (纸本)9781624106101

The demand in the logistics market is vast, but its revenue is relatively small. This fact forces the need for optimized operation in logistics delivery. Several algorithms have been proposed to solve simple delivery problems. An algorithm that can solve a delivery problem in a hybrid-transit network and consider the collaboration between heterogeneous agents is needed to optimize the operation further. This paper proposed an algorithm called Vehicle Routing Problem with Pickup, Relay, and Delivery (VRP-PRD) to solve the delivery problem in the hybrid-transit network by considering the physical constraints of the heterogeneous delivery vehicles with several objective functions. The simulation results also show that VRP-PRD can solve the problem with a reasonable computing time.

关键词： Logistics Network Computing Time mixed integer linear programming linear programming MATLAB

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SALEM: Service Fairness in Wireless Mesh Environments

SALEM: Service Fairness in Wireless Mesh Environments

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Henrique Silva Noé Godinho Bruno Sousa DEI CISUC University of Coimbra Coimbra Portugal

The utilisation of resources from a fairness perspective has been an extensively researched topic, either to enhance the quality of services or to allow spectrum sharing, among others. One method to define forwarding routes is through flow algorithms, which aim to find optimal paths between nodes where capacity constraints are of interest. SALEM is an approach to enable fairness in services competing for resources in wireless mesh environments. SALEM implements a multicommodity flow heuristic, based on a mixed integer linear programming (MILP) formulation, to consider fairness in reliability, delay and energy objectives and is constrained by bandwidth and link usage criteria. SALEM is implemented in the ONOS controller to enable a fair utilisation of links in a topology replicating a real-world scenario. Within a time complexity that is directly related to the topology, the number of users and available services, the results of SALEM demonstrate its feasibility to run in production-ready networks with minimal overhead.

关键词： Wireless communication Network topology Quality of service Bandwidth Topology Delays mixed integer linear programming

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