Title :
Minimizing risk on a fleet mix problem with a multiobjective evolutionary algorithm
Author :
Mazurek, Michael ; Wesolkowski, Slawomir
Author_Institution :
OR Team, Canadian Forces Aerosp. Warfare Centre, Ottawa, ON, Canada
Abstract :
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.
Keywords :
Monte Carlo methods; Pareto optimisation; genetic algorithms; military vehicles; risk management; transportation; Monte Carlo-based model; NSGA-II; Pareto-optimal; SaFE model; fleet mix problem; military; multiobjective evolutionary algorithm; multiobjective optimization; nondominated sorting genetic algorithm-II; risk minimization; stochastic fleet estimation; total task duration time; vehicle fleet; Computational intelligence; Cost function; Evolutionary computation; Frequency; Organizations; Security; Stochastic processes; Testing; Uncertainty; Vehicle safety;
Conference_Titel :
Computational Intelligence for Security and Defense Applications, 2009. CISDA 2009. IEEE Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4244-3763-4
Electronic_ISBN :
978-1-4244-3764-1
DOI :
10.1109/CISDA.2009.5356525
