@inproceedings {pub3830,
	title = {Vehicle Fleet Maintenance Scheduling by Multi-objective Evolutionary Algorithms},
	author = {Yali Wang AND Steffen Limmer AND Markus Olhofer AND Michael Emmerich AND Thomas B{\"a}ck},
	year = {2019},
	month = {July},
	abstract = {In this paper, a new real-world application problem, i.e., the vehicle fleet maintenance scheduling optimization problem, is defined and a specialized multi-objective evolutionary algorithm framework (grouping strategy, three vector chromosome and corresponding genetic operators) is proposed to solve the problem. State-of-the-art multi-objective evolutionary algorithms
such as NSGA-III, SMS-EMOA, DI-MOEA are employed in the proposed algorithm framework to solve the problem, and their behavior is investigated. Although DI-MOEA is used the first time for a real-world application problem, its performance is better than other algorithms for some instances.},
	publisher = {IEEE},
	booktitle = {2019 IEEE Congress on Evolutionary Computation (CEC)},
	pages = {442-449}
}