Automated solution selection in multi-objective optimisation

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Automated solution selection in multi-objective optimisation
This paper proposes an approach to the solution of multi-objective optimisation problems that delivers a single, preferred solution. A conventional, population-based, multiobjective optimisation method is used to provide a set of solutions approximating the Pareto front. As the set of solutions evolves, an approximation to the Pareto front is derived using a Kriging method. This approximate surface is traversed using a single objective optimisation method, driven by a simple, aggregated objective function that expresses design preferences. The approach is demonstrated using a combination of multi-objective particle swarm optimisation (MOPSO) and the Simplex method of Nelder and Mead, applied to several, standard, multi-objective test problems. Good, compromise solutions meeting user-defined design preferences are delivered without manual intervention.
Andrew Lewis, David Ireland
Added 18 Oct 2010
Updated 18 Oct 2010
Type Conference
Year 2008
Where CEC
Authors Andrew Lewis, David Ireland
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