Optimization model for electric aircraft tow tractors scheduling under operator cooperation

IF 7.6 1区 工程技术 Q1 TRANSPORTATION SCIENCE & TECHNOLOGY
Dan-Wen Bao , Jia-Yi Zhou , Di Kang , Zhuo Chen
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引用次数: 0

Abstract

Collaborating among operators can significantly reduce transportation costs—a concept already proven in the logistics industry. With growing transportation demand and the added complexity of electric vehicle (EV) charging times, airport ground support services face increasing pressure to optimize operations. This study introduces a novel concept of operator-cooperate mode for airport ground support services for the first time, where operators share vehicle fleets to enhance efficiency. This paper develops vehicle scheduling and cost allocation methods under the cooperation framework. Two models are established for scheduling electric tow tractors: one for the traditional operator-separate mode and another for the operator-cooperate mode. Using an adaptive large neighborhood search framework, algorithms are designed to generate scheduling plans that minimize costs and delays. To support cooperation, the study proposes a cost allocation method that considers differentiated unit delay costs and level of sharing among operators to ensure the feasibility and fairness of cooperation. Finally, numerical experiments are conducted based on one day of flight schedule data from a major international airport, validating the effectiveness of the algorithm and cost allocation method across 21 experimental scenarios. The results show that the algorithm delivers solutions faster than traditional solvers while keeping the weighted objective function gap within 2%.Moreover, the improved cost allocation method ensures greater fairness than the traditional Shapley method. The numerical experiments indicate that cooperation can save 5–16% in operating costs and 15–33% in delay times for airports, with the savings varying based on the sharing parameters. The study also uses sensitivity analysis and other quantitative methods to examine changes in overall and individual cooperated utility changes. It provides recommendations and decision-making strategies for configuring and managing airport ground operations.
驾驶员合作下电动飞机拖曳机调度优化模型
运营商之间的合作可以显著降低运输成本,这一概念已在物流业得到证实。随着交通需求的增长和电动汽车充电时间的增加,机场地面保障服务面临着越来越大的优化运营压力。本研究首次为机场地面保障服务引入了运营商-合作模式的新概念,运营商共享车队以提高效率。本文研究了合作框架下的车辆调度和成本分摊方法。建立了两种电动拖车调度模型:传统的操作员分离调度模型和操作员协作调度模型。采用自适应大邻域搜索框架,设计算法生成成本和延迟最小的调度计划。为了支持合作,本研究提出了一种考虑差异化单位延迟成本和运营商间分担水平的成本分配方法,以保证合作的可行性和公平性。最后,以某主要国际机场一天的航班时刻表数据为例进行了数值实验,在21个实验场景中验证了算法和成本分摊方法的有效性。结果表明,该算法在保证加权目标函数差在2%以内的情况下,求解速度比传统算法快。改进后的成本分配方法比传统的Shapley方法更具公平性。数值实验表明,合作可以节省5-16%的运营成本和15-33%的延误时间,并且根据共享参数的不同而有所不同。本研究还采用敏感性分析等定量方法考察整体和个体合作效用变化。它为配置和管理机场地面操作提供建议和决策策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
15.80
自引率
12.00%
发文量
332
审稿时长
64 days
期刊介绍: Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.
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