Multiobjective Optimization Approaches to Airline Crew Rostering Problems: A Case Study
Document Type
Conference Proceeding
Publication Date
12-4-2018
Abstract
This work investigates an airline crew rostering problem derived from a real practice of a large airline company in China. The problem has the characteristics of large scale, complex constraints and multiple objectives. Three multiobjective evolutionary algorithms are developed to seek a set of approximated Pareto optimal solutions. The algorithms are verified via several groups of instances extracted from a realworld airline's operational data. The computational results can help us gain insight into how to make better trade-off decisions among different objectives.
Identifier
85059986892 (Scopus)
ISBN
[9781538635933]
Publication Title
IEEE International Conference on Automation Science and Engineering
External Full Text Location
https://doi.org/10.1109/COASE.2018.8560581
e-ISSN
21618089
ISSN
21618070
First Page
750
Last Page
755
Volume
2018-August
Grant
71601191
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Zhang, Zizhen; Zhou, Mengchu; and Guo, Songshan, "Multiobjective Optimization Approaches to Airline Crew Rostering Problems: A Case Study" (2018). Faculty Publications. 8174.
https://digitalcommons.njit.edu/fac_pubs/8174
