An Improved Particle Swarm Optimization Algorithm for Irregular Flight Recovery Problem
13th International Conference on Swarm Intelligence, ICSI 2022
; 13344 LNCS:190-200, 2022.
Article
in English
| Scopus | ID: covidwho-1958899
ABSTRACT
As with the rapid development of air transportation and potential uncertainties caused by abnormal weather and other emergencies, such as Covid-19, irregular flights may occur. Under this situation, how to reduce the negative impact on airlines, especially how to rearrange the crew for each aircraft, becomes an important problem. To solve this problem, firstly, we established the model by minimizing the cost of crew recovery with time-space constraints. Secondly, in view of the fact that crew recovery belongs to an NP-hard problem, we proposed an improved particle swarm optimization (PSO) with mutation and crossover mechanisms to avoid prematurity and local optima. Thirdly, we designed an encoding scheme based on the characteristics of the problem. Finally, to verify the effectiveness of the improved PSO, the variant and the original PSO are used for comparison. And the experimental results show that the performance of the improved PSO algorithm is significantly better than the comparison algorithms in the irregular flight recovery problem covered in this paper. © 2022, Springer Nature Switzerland AG.
Crew recovery; Cross-over mechanism; Irregular flight; Mutation mechanism; Particle swarm algorithm; Computational complexity; Particle swarm optimization (PSO); Recovery; Crew recoveries; Cross-over; Improved particle swarm optimization algorithms; Particle swarm; Swarm optimization; Uncertainty; Air transportation
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Scopus
Language:
English
Journal:
13th International Conference on Swarm Intelligence, ICSI 2022
Year:
2022
Document Type:
Article
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