Affiliations: [a] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China
| [b] National United Engineering Laboratory of Integrated and Intelligent Transportation, Southwest Jiaotong University, Chengdu, China
Correspondence:
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Corresponding author. Yan Yan. E-mail: [email protected].
Abstract: 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.
Keywords: Aircraft fleet route optimization, multi-airbases stochastic, time and capacity constraints, improved NSGA-II algorithm
