Multiobjective Optimization Approaches to Airline Crew Rostering Problems: A Case Study

Zizhen Zhang, Mengchu Zhou, Songshan Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PublisherIEEE Computer Society
Pages750-755
Number of pages6
ISBN (Electronic)9781538635933
DOIs
StatePublished - Dec 4 2018
Event14th IEEE International Conference on Automation Science and Engineering, CASE 2018 - Munich, Germany
Duration: Aug 20 2018Aug 24 2018

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2018-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Other

Other14th IEEE International Conference on Automation Science and Engineering, CASE 2018
CountryGermany
CityMunich
Period8/20/188/24/18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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