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Multiobjective evolutionary algorithm with risk minimization applied to a fleet mix problem

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3 Author(s)
Willick, K. ; Canadian Forces Aerosp. Warfare Centre OR Team in Ottawa, Ottawa, ON, Canada ; Wesolkowski, S. ; Mazurek, M.

We apply the non-dominated sorting genetic algorithm-II (NSGA-II) to a multi-objective fleet-mix problem for risk mitigation. The Stochastic Fleet Estimation (SaFE) model, a Monte Carlo-based model, is used to determine average annual requirements which a fleet must meet. We search for Pareto-optimal combinations of platform-to-task assignments that can be used to complete SaFE generated scenarios. Solutions are evaluated using three objectives, with a goal of minimizing fleet cost, total task duration, and the risk that a solution will not be able to accomplish future scenarios. Optimization over all three objectives allowed for exploration of configurations which were low cost and low risk, a region not explored by prior experiments without the risk objective.

Published in:

Evolutionary Computation (CEC), 2010 IEEE Congress on

Date of Conference:

18-23 July 2010