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IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)

作者： Cong, Xiangyue Yang, Bo Gao, Fengkun Chen, Cailian Tang, Yuliang Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Shanghai Engn Res Ctr Ind Intelligent Control & M Shanghai 200240 Peoples R China Xiamen Univ Dept Informat & Commun Engn Xiamen 361005 Peoples R China

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

The emergence of connected and automated vehicles (CAVs) poses a promising future of transportation systems. Complicated traffic conditions at intersections lead to challenges for cooperative driving of CAVs while ensuring safety and efficiency. This paper proposes a conflict-free cooperative control method for CAVs at unsignalized intersections. Based on the conflict points inside the intersection, we project each conflict vehicles cluster onto one virtual lane and construct multiple virtual platoons for ensuring safety. To maximize the intersection utilization, a packing problem is proposed for developing optimal car-following order, which is formulated as a mixed-integer linear programming (MILP). Considering the practical conditions at the intersection, we remove the redundant constraints to obtain nearly global-optimal solutions in real time. Numerical simulations validate that the proposed method saves 5.5%-9.3% total evacuation time under normal traffic flow.

关键词： Transportation Numerical simulation Real-time systems Safety mixed integer linear programming

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Simultaneous Charger Placement and Power Scheduling for On-Demand Provisioning of RF Wireless Charging Service 21st

Simultaneous Charger Placement and Power Scheduling for On-D...

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21st International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Jiang, Huatong Li, Yanjun Gao, Meihui Zhejiang Univ Technol Sch Comp Sci & Technol Hangzhou Peoples R China

ISBN: (纸本)9783030953881;9783030953874

To provision on-demand radio frequency (RF) charging service in a designated place, the problem of simultaneous charger placement and power scheduling is studied. Based on users' historic spatial and temporal distribution information, we formulate the problem as how to place a given number of chargers and how to adjust the chargers' power levels in each time interval so that the revenue of the charging service can be maximized, given the total power limitation constraint. The formulated problem is a mixed integer linear programming (MILP) problem and we propose a branch and bound (B&B) algorithm to solve it. Extensive simulations in both small-scale and large-scale networks, as well as simulations based on the real data set are conducted to validate the effectiveness of our proposed algorithm. The results show that, our proposed algorithm outperforms greedy algorithm, an algorithm that deals charger placement and power scheduling separately, in most of the simulation scenarios, and reaches the optimum in small-scale instances.

关键词： RF charging Charger placement Power scheduling mixed integer linear programming

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Potential of Formation Flight for Commercial Aviation: Three Case Studies

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JOURNAL OF AIRCRAFT 2021年第2期58卷 320-333页

作者： Kent, Thomas E. Richards, Arthur G. Univ Bristol Dept Comp Sci Queens Bldg Bristol BS8 1TR Avon England Univ Bristol Dept Engn Dynam & Control Queens Bldg Bristol BS8 1TR Avon England

Formation flight has the potential to significantly reduce aircraft fuel consumption by allowing "follower" aircraft to fly in the aerodynamic wake of "leader" aircraft. However, this requirement for aircraft to be in close proximity for large parts of their journey raises questions about the suitability of flying in formation given the diverse range of existing flights and geographical regions. This paper demonstrates the potential for two-aircraft formation flight for three distinct case studies: long-haul airline, transatlantic airline, and low-cost airline, encompassing a range of typical airline regions and characteristics. The results indicate, even with only minor scheduling alterations, the potential fuel savings could result in saving hundreds of millions of dollars in fuel costs and reducing millions of tonnes of carbon dioxide emissions. An analytical geometric method for calculating all possible combinations of optimal routes is presented. This is coupled with a mixed integer linear program for providing an assignment of aircraft into formation pairs. A number of different key metrics, correlations, and predictive indicators help to determine which flights, airlines, and regions show "good" formation potential. Importantly, this paper also demonstrates these results for a wide range of drag-reduction possibilities and the impact this has on achievable fuel saving.

关键词： Commercial Aviation Aerodynamic Simulation Direct Operating Cost mixed integer linear programming Fuel Consumption Transatlantic Flight Flight Testing Wake Vortices Base of Aircraft Data Burning Rate

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On the optimized design of next-generation wind farms

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2021年第3期291卷 862-870页

作者： Fischetti, Martina Vattenfall BA Wind Havneholmen 29 DK-1561 Copenhagen Denmark

A transformation from fossil fuels to renewable energy has been ongoing in recent years, driven by growing environmental and sustainability demands from customers and society. An increased use of renewable sources can, in particular, help during climate change, which is a very sensitive topic right now. Because demand for green energy is increasing, while competition is also growing, innovation and optimization are of key importance in this business. In particular, because the offshore wind energy market is based on an auction system: the company that can construct and operate the farm with the lowest subsidies will win the auction and capitalize on its investment. It is therefore extremely important to both minimize costs and increase profits at the design phase of new farms. In this paper we will illustrate how Operational Research techniques can help companies be more competitive on the market. To be specific, we address two of the main design challenges arising in the design of new offshore wind farms, the optimal allocation of wind turbines (to minimize interference between them and position-related costs) and their electrical interconnection. We show that a synergic use of mixed integer programming models and heuristic methods in the so-called matheuristic framework can be used to solve both problems efficiently. The optimization tools that we will describe have been used also for the design of Hollande Kust Zuid, the first offshore wind farm in the world to be constructed subsidy-free. We report results on a number of real instances, showing the impact of these techniques in decreasing costs and increasing profitability, with average gains of more than (sic) 10 M for each wind farm. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Combinatorial optimization OR in energy OR in environment and climate change Wind farm design mixed integer linear programming

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Optimal Operation of Virtual Power Plant with Considering the Demand Response and Electric Vehicles

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JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2021年第5期16卷 2407-2419页

作者： Heydari, Rana Nikoukar, Javad Gandomkar, Majid Islamic Azad Univ Coll Elect Engn & Comp Dept Elect Engn Saveh Branch Saveh Iran

The needs of human communities for electrical energy is increasing every day, and as a result, the price of fossil fuels is steadily increasing. Considering the trend of advances in renewable energy technologies and the support of governments and energy policymakers to make more use of these clean and inexpensive resources. Limitations such as low capacity, the uncertainty of output power and stability issues have made it costly and difficult to use Distributed Energy Resources (DERs). To solve these problems, a new concept known as Virtual Power Plant (VPP) has been proposed to facilitate the exploitation of DERs. The VPP is a set of DERs that are put together for market participation. Also, efforts to reduce the amount of environmental pollution have replaced the use of Electric Vehicles (EV) instead of internal combustion engines. Regarding this paper, a new model for optimizing virtual power plant is presented. In this model, the Demand response (DR) has been used, whose modeling is based on Price-Based Demand Response for ordinary loads and incentive. To solve the problem a mixed integer linear programming model is proposed to maximize the profit of the virtual power plant. In order to see the effectiveness and satisfying performance of proposed model, a case study including DERs, EV, and loads is studied as test system. The simulation results using Matlab and GAMS show the efficiency of the proposed model and proves that simultaneous use of the price-based demand response program, smart charging, and the participation of electric vehicles in demand responses reduces operating costs.

关键词： Virtual power plant Electric vehicles Distributed generation resources Demand response mixed integer linear programming

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Optimal Sizing of Smart Home Renewable Energy Resources and Battery Under Prosumer-Based Energy Management

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IEEE SYSTEMS JOURNAL 2021年第1期15卷 105-113页

作者： Bhamidi, Lokeshgupta Sivasubramani, S. Indian Inst Technol Dept Elect Engn Patna 801106 Bihar India

This article presents the framework of a two-stage optimization model for the optimal planning of smart home renewable energy resources (RERs) and battery integration with the association of prosumer-based energy management. The optimal sizing problem of in-house RERs and battery is addressed in the first-stage optimization with the objective function of RERs and battery's total life-cycle cost minimization. The smart home daily energy operation problem is formulated in the second stage with the help of multiobject home energy management (MOHEM). In the second-stage operation problem, the MOHEM is implemented with two different objective functions such as minimization of consumer's daily energy cost and maximization of consumer's total comfort level index. The particle swarm optimization algorithm and a mixed-integer linear programming technique are, respectively, used in this article to optimize the proposed two-stage optimization model. A typical smart home which consists of various controllable appliances is considered in this analysis to evaluate the performance of the proposed two-stage optimization model. Three different case studies are considered in the simulation to assess the effectiveness of the proposed model. Finally, an economic analysis is also done in this article to examine the smart home consumer's capital investment benefits.

关键词： Smart homes Batteries Energy management Optimization Home appliances Load modeling Planning Fuzzy satisfaction-maximizing method mixed integer linear programming optimal smart home renewable and battery sizing prosumer-based energy management two-stage optimization method

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A more efficient cutting planes approach for the green vehicle routing problem with capacitated alternative fuel stations

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OPTIMIZATION LETTERS 2021年第8期15卷 2813-2829页

作者： Bruglieri, Maurizio Mancini, Simona Pisacane, Ornella Politecn Milan Dipartimento Design Milan Italy Univ Klagenfurt Dept Operat Energy & Environm Management Klagenfurt Austria Univ Politecn Marche Dipartimento Ingn Informaz Ancona Italy

The Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations assumes that, at each station, the number of vehicles simultaneously refueling cannot exceed the number of available pumps. The state-of-the-art solution method, based on the generation of all feasible non-dominated paths, performs well only with up to 2 pumps. In fact, it needs cloning the paths between every pair of pumps. To overcome this issue, in this paper, we propose new path-based MILP models without cloning paths, for both the scenario with private stations (i.e., owned by the fleet manager) and that with public stations. Then, a more efficient cutting plane approach is designed for addressing both the scenarios. Numerical results, obtained considering a set of benchmark instances ad hoc generated for this work, show both the efficiency and the effectiveness of this new cutting plane approach proposed. Finally, a sensitivity analysis, carried out by varying the number of customers to be served and their distribution, shows very good performances of the proposed approach.

关键词： Vehicle routing problem Alternative fuel vehicles mixed integer linear programming Fueling pump reservation

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Fast-Time Demand-Capacity Balancing Optimizer for Collaborative Air Traffic Flow Management

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2021年第8期18卷 583-595页

作者： Xu, Yan Camargo, Leonardo Prats, Xavier Cranfield Univ Sch Aerosp Transport & Mfg Bldg 320Coll Rd Bedford MK43 0AL England Tech Univ Catalonia Dept Phys Aerosp Div Off C3-121Esteve Terradas 5 Barcelona 08860 Spain

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A multivariate migrating birds optimization algorithm based on disjunctive graph neighborhood for scenic spot vehicle scheduling

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APPLIED SOFT COMPUTING 2024年 163卷

作者： Fei, Rong Wang, Zilong Li, Junhuai Zhang, Facun Peng, Hailong Cheng, Junzhi Xian Univ Technol Sch Comp Sci & Engn Xian Shaanxi Peoples R China Shaanxi Key Lab Network Comp & Secur Technol Xian Shaanxi Peoples R China

For the group travel, reasonable vehicle scheduling needs to consider constraints such as traffic distance and route conflict, which is common in many vehicle transportation scheduling systems, and it is crucial for operators to improve operational efficiency and provide a higher quality service experience. In this paper, a scenic spot vehicle scheduling problem is designed based the real-world scenario. In order to improve the search efficiency and maintain the diversity of solutions , an intelligent scheduling algorithm based on improved migrating birds optimization(gMBO) is proposed. The gMBO applies a neighborhood structure based on disjunctive graph to accelerate the solution search in the touring phase by avoiding redundancy. Besides, leveraging the left-right sequential queue characteristics of the MBO algorithm, gMBO utilizes two mechanisms to enhance the interaction between queues in the leader replacement stage, which can expand the search space of solutions and at the same time to maintain population diversity . Finally, we consider using the POX crossover operator in the individual, it is well adapted to the characteristics of the problem can reduce the generation of unreasonable solutions. The computational results show that the neighborhood structure is feasible. Considering the problem of scenic spot vehicle scheduling in practical urban applications, the multivariate migrating birds optimization algorithm based on disjunctive graph neighborhood is more effective than the MILP and other three meta-heuristic algorithms, and the optimal solution is obtained under the same stopping criteria, with an average RPD of 2.16. It has the advantages of fast convergence and good robustness.

关键词： mixed integer linear programming Migrating birds optimization Vehicle scheduling Combinatorial optimization Meta-heuristic algorithm

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Adaptive robust electric vehicle routing under energy consumption uncertainty

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2024年 160卷

作者： Jeong, Jaehee Ghaddar, Bissan Zufferey, Nicolas Nathwani, Jatin Univ Waterloo Dept Management Sci Waterloo ON Canada Ivey Business Sch London London ON Canada Tech Univ Denmark Dept Technol Management & Econ Lyngby Denmark Univ Geneva Geneva Sch Econ & Management Geneva Switzerland

Electric vehicles (EVs) have been highly favoured as a mode of transportation in recent years. EVs offer numerous benefits over traditional fuel -based vehicles, particularly in terms of the environmental impact. Although electric vehicles offer several advantages, there are certain restrictions that limit their usage. One of the significant issues is the uncertainty in their driving range. The driving range of EVs is closely related to their energy consumption, which is highly affected by exogenous and endogenous factors. Since those factors are unpredictable, uncertainty in EVs' energy consumption should be considered for efficient operation. This paper proposes a two -stage adaptive robust optimization framework for the electric vehicle routing problem. The objective is to minimize the worst -case energy consumption while guaranteeing that services are delivered at the appointed time windows without battery level deficiency. We postulate that EVs can be recharged on route, and the charging amount can be adjusted depending on the circumstances. A column -and -constraint generation based heuristic algorithm, which is coupled with variable neighbourhood search and alternating direction algorithm, is proposed to solve the resulting model. The computational results show the economic efficiency and robustness of the proposed model, and that there is a tradeoff between the total required energy and the risk of failing to satisfy all customers' demand.

关键词： Adaptive robust optimization Electric vehicle routing Uncertainty Decomposition mixed integer linear programming

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