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Aircraft fleet route optimization based on cost and low carbon emission in aviation line alliance network

机译:航空公司联盟网络中成本和低碳排放的飞机车队路线优化

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This paper studies the flight path optimization problem of air cargo companies in aviation line alliance. There are two limitations in this paper. One is to limit of the number and location of airbases and capacity in the air network. The other is to limit of flight time and airspace capacity of full cargo aircraft in actual operation. Considering the influence of alliance on operation, the selection probability of air alliance is introduced. It is assuming that all cargo aircraft is one type, the unit transportation cost of every aviation line is the same as each other, the queuing problem of aircraft landing is not considered, and the network transportation demand of itself must be completed by an airline. It proposes a directed aircraft fleet routing problem optimization model (SMDDDAAAFRPTW) with multi-airbase stochastic and time constraints to minimize total operating cost and flight distance. Using the multi-objective optimization algorithm NSGA-II by most scholars, and improving the initial solution generation step, introducing Genetic engineering into cross-mutation to solve the optimal number and location of air bases and fleet routing of multiple aircraft. Comparing with the weighted method and ant colony algorithm, it shows that the improved NSGA-II algorithm is effective and has better computational efficiency. The results show that the more segments are selected for outsourcing, the lowest cost of network and the lowest carbon emission. This kind of decision-making behavior is only suitable for the initial operation phase of the enterprise.
机译:本文研究了航空线联盟航空货运公司的飞行路径优化问题。本文有两个局限性。一个是限制空气纸板的数量和位置和空中网络中的容量。另一个是在实际操作中限制全货运飞机的飞行时间和空域能力。考虑到联盟对运行的影响,介绍了空气联盟的选择概率。假设所有货运飞机都是一种类型,每个航空线的单位运输成本都与彼此相同,不考虑飞机着陆的排队问题,并且网络运输需求本身必须由航空公司完成。它提出了一架定向飞机舰队路由问题优化模型(SMDDDAAAFRPTW),具有多空气级随机和时间约束,以最大限度地减少总运营成本和飞行距离。大多数学者使用多目标优化算法NSGA-II,提高初始解决方案生成步骤,将遗传工程引入交叉突变以解决多种飞机的空气基座的最佳数量和位置。与加权方法和蚁群算法进行比较,表明改进的NSGA-II算法是有效的,具有更好的计算效率。结果表明,选择更多的段用于外包,网络成本最低和最低碳排放。这种决策行为仅适用于企业的初始操作阶段。

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