Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Operations Research
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
The Stochastic Fleet Estimation (SaFE) model
Proceedings of the 2008 Spring simulation multiconference
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Proceedings of the 2010 Summer Computer Simulation Conference
A fuzzy evolutionary simulation model (FESModel) for fleet combat strategies
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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We apply the non-dominated sorting genetic algorithm-II (NSGA-II) to perform a multiobjective optimization of the Stochastic Fleet Estimation (SaFE) model. SaFE is a Monte Carlo-based model which generates a vehicle fleet based on the set of requirements that the fleet is supposed to accomplish. We search for Pareto-optimal combinations of valid platform-assignments for a list of tasks, which can be applied to complete scenarios output by SaFE. Solutions are evaluated on three objectives, with the goal of minimizing fleet cost, total task duration time, and the risk that a solution will not be able to accomplish possible future scenarios.