scholarly journals Flight schedule adjustment for hub airports using multi-objective optimization

2021 ◽  
Vol 30 (1) ◽  
pp. 931-946
Author(s):  
Mei Tao ◽  
Lan Ma ◽  
Yiming Ma

Abstract Based on the concept of “passengers self-help hubbing,” we build a flight schedule optimization model where maximizing the number of feasible flight connections, indicating transfer opportunities, as one objective and minimizing total slot displacements as the other objective. At the same time, the “Demand Smoothing Model” is introduced into the flight schedule optimization model to reduce the queuing delays for arrival and departure flights. We take into account all aircraft itineraries, the difficulty level of schedule coordination, and the maximum displacement of any single flight acceptable to airlines when optimizing flight schedule. Given an original schedule, the model produces a feasible modified schedule that obeys the slot limits specified for an airport without canceling any flights, increases transfer opportunities, and improves on-time performance for hub airports while reducing interference with airline scheduling preferences. The model was verified with the operating data of the Urumqi international airport, and the results show that minor adjustments to flight schedules can increase the transfer opportunities of the airport and significantly reduce flight queuing delays.

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.


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