Abstract
Conference Title: 2018 IEEE 14th International Conference on Automation Science and Engineering (CASE) Conference Start Date: 2018, Aug. 20 Conference End Date: 2018, Aug. 24 Conference Location: Munich, Germany 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.