Applying hybrid multiobjective evolutionary algorithms to the sailor assignment problem
Abstract
This chapter investigates a multiobjective formulation of the United States Navy's Sailor Assignment Problem (SAP) and examines the performance of two widely-used multiobjective evolutionary algorithms (MOEAs) on large instances of this problem. The performance of the algorithms is examined with respect to both solution quality and diversity, and the algorithms are shown to provide inadequate diversity along the Pareto front. A domain-specific local improvement operator is introduced into the MOEAs, producing significant performance increases over the evolutionary algorithms alone. This hybrid MOEA approach is applied to the sailor assignment problem and shown to provide greater diversity along the Pareto front. The manner in which the local search is incorporated differs somewhat from what is generally reported. Our results suggest that such an approach may be beneficial for practitioners in handling similar types of real-world problems. © 2007 Springer-Verlag Berlin Heidelberg.
Publication Title
Studies in Computational Intelligence
Recommended Citation
Garrett, D., Dasgupta, D., Vannucci, J., & Simien, J. (2007). Applying hybrid multiobjective evolutionary algorithms to the sailor assignment problem. Studies in Computational Intelligence, 66, 269-301. https://doi.org/10.1007/978-3-540-72377-6_12
